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• Published: 16 March 2021

5G mobile networks and health—a state-of-the-science review of the research into low-level RF fields above 6 GHz

• Ken Karipidis   ORCID: orcid.org/0000-0001-7538-7447 1 ,
• Rohan Mate 1 ,
• David Urban 1 ,
• Rick Tinker 1 &
• Andrew Wood 2  

Journal of Exposure Science & Environmental Epidemiology volume  31 ,  pages 585–605 ( 2021 ) Cite this article

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The increased use of radiofrequency (RF) fields above 6 GHz, particularly for the 5 G mobile phone network, has given rise to public concern about any possible adverse effects to human health. Public exposure to RF fields from 5 G and other sources is below the human exposure limits specified by the International Commission on Non-Ionizing Radiation Protection (ICNIRP). This state-of-the science review examined the research into the biological and health effects of RF fields above 6 GHz at exposure levels below the ICNIRP occupational limits. The review included 107 experimental studies that investigated various bioeffects including genotoxicity, cell proliferation, gene expression, cell signalling, membrane function and other effects. Reported bioeffects were generally not independently replicated and the majority of the studies employed low quality methods of exposure assessment and control. Effects due to heating from high RF energy deposition cannot be excluded from many of the results. The review also included 31 epidemiological studies that investigated exposure to radar, which uses RF fields above 6 GHz similar to 5 G. The epidemiological studies showed little evidence of health effects including cancer at different sites, effects on reproduction and other diseases. This review showed no confirmed evidence that low-level RF fields above 6 GHz such as those used by the 5 G network are hazardous to human health. Future experimental studies should improve the experimental design with particular attention to dosimetry and temperature control. Future epidemiological studies should continue to monitor long-term health effects in the population related to wireless telecommunications.

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Introduction

There are continually emerging technologies that use radiofrequency (RF) electromagnetic fields particularly in telecommunications. Most telecommunication sources currently operate at frequencies below 6 GHz, including radio and TV broadcasting and wireless sources such as local area networks and mobile telephony. With the increasing demand for higher data rates, better quality of service and lower latency to users, future wireless telecommunication sources are planned to operate at frequencies above 6 GHz and into the ‘millimetre wave’ range (30–300 GHz) [ 1 ]. Frequencies above 6 GHz have been in use for many years in various applications such as radar, microwave links, airport security screening and in medicine for therapeutic applications. However, the planned use of millimetre waves by future wireless telecommunications, particularly the 5th generation (5 G) of mobile networks, has given rise to public concern about any possible adverse effects to human health.

The interaction mechanisms of RF fields with the human body have been extensively described and tissue heating is the main effect for RF fields above 100 kHz (e.g. HPA; SCENHIR) [ 2 , 3 ]. RF fields become less penetrating into body tissue with increasing frequency and for frequencies above 6 GHz the depth of penetration is relatively short with surface heating being the predominant effect [ 4 ].

International exposure guidelines for RF fields have been developed on the basis of current scientific knowledge to ensure that RF exposure is not harmful to human health [ 5 , 6 ]. The guidelines developed by the International Commission on Non-Ionizing Radiation Protection (ICNIRP) in particular form the basis for regulations in the majority of countries worldwide [ 7 ]. In the frequency range above 6 GHz and up to 300 GHz the ICNIRP guidelines prevent excessive heating at the surface of the skin and in the eye.

Although not as extensively studied as RF fields at lower frequencies, a number of studies have investigated the effects of RF fields at frequencies above 6 GHz. Previous reviews have reported studies investigating frequencies above 6 GHz that show effects although many of the reported effects occurred at levels greater than the ICNIRP guidelines [ 1 , 8 ]. Given the public concern over the planned roll-out of 5 G using millimetre waves, it is important to determine whether there are any related adverse health consequences at levels encountered in the environment. The aim of this paper is to present a state-of-the-science review of the bioeffects research into RF fields above 6 GHz at low levels of exposure (exposure below the occupational limits of the ICNIRP guidelines). A meta-analysis of in vitro and in vivo studies, providing quantitative effect estimates for each study, is presented separately in a companion paper [ 9 ].

The state-of-the-science review included a comprehensive search of all available literature and examined the extent, range and nature of evidence into the bioeffects of RF fields above 6 GHz, at levels below the ICNIRP occupational limits. The review consisted of biomedical studies on low-level RF electromagnetic fields from 6 GHz to 300 GHz published at any starting date up to December 2019. Studies were initially found by searching the databases PubMed, EMF-Portal, Google Scholar, Embase and Web of Science using the search terms “millimeter wave”, “millimetre wave”, “gigahertz”, “GHz” and “radar”. We further searched major reviews published by health authorities on RF and health [ 2 , 3 , 10 , 11 ]. Finally, we searched the reference list of all the studies included. Studies were only included if the full paper was available in English.

Although over 300 studies were considered, this review was limited to experimental studies (in vitro, in vivo, human) where the stated RF exposure level was at or below the occupational whole-body limits specified by the ICNIRP (2020) guidelines: power density (PD) reference level of 50 W/m 2 or specific absorption rate (SAR) basic restriction of 0.4 W/kg. Since the PD occupational limits for local exposure are more relevant to in vitro studies, and since these limits are higher, we have included those studies with PD up to 100–200 W/m 2 , depending on frequency. The review included studies below the ICNIRP general public limits that are lower than the occupational limits.

The review also included epidemiological studies (cohort, case-control, cross-sectional) investigating exposure to radar but excluded studies where the stated radar frequencies were below 6 GHz. Epidemiological studies on radar were included as they represent occupational exposure below the ICNIRP guidelines. Case reports or case series were excluded. Studies investigating therapeutical outcomes were also excluded unless they reported specific bio-effects.

The state-of-the-science review appraised the quality of the included studies, but unlike a systematic review it did not exclude any studies based on quality. The review also identified gaps in knowledge for future investigation and research. The reporting of results in this paper is narrative with tabular accompaniment showing study characteristics. In this paper, the acronym “MMWs” (or millimetre waves) is used to denote RF fields above 6 GHz.

The review included 107 experimental studies (91 in vitro, 15 in vivo, and 1 human) that investigated various bioeffects, including genotoxicity, cell proliferation, gene expression, cell signalling, membrane function and other effects. The exposure characteristics and biological system investigated in experimental studies for the various bioeffects are shown in Tables  1 – 6 . The results of the meta-analysis of the in vitro and in vivo studies are presented separately in Wood et al. [ 9 ].

Genotoxicity

Studies have examined the effects of exposing whole human or mouse blood samples or lymphocytes and leucocytes to low-level MMWs to determine possible genotoxicity. Some of the genotoxicity studies have looked at the possible effects of MMWs on chromosome aberrations [ 12 , 13 , 14 ]. At exposure levels below the ICNIRP limits, the results have been inconsistent, with either a statistically significant increase [ 14 ] or no significant increase [ 12 , 13 ] in chromosome aberrations.

MMWs do not penetrate past the skin therefore epithelial and skin cells have been a common model of examination for possible genotoxic effects. DNA damage in a number of epithelial and skin cell types and at varied exposure parameters both below and above the ICNIRP limits have been examined using comet assays [ 15 , 16 , 17 , 18 , 19 ]. Despite the varied exposure models and methods used, no statistically significant evidence of DNA damage was identified in these studies. Evidence of genotoxic damage was further assessed in skin cells by the occurrence of micro-nucleation. De Amicis et al. [ 18 ] and Franchini et al. [ 19 ] reported a statistically significant increase in micro-nucleation, however, Hintzsche et al. [ 15 ] and Koyama et al. [ 16 , 17 ] did not find an effect. Two of the studies also examined telomere length and found no statistically significant difference between exposed and unexposed cells [ 15 , 19 ]. Last, a Ukrainian research group examined different skin cell types in three studies and reported an increase in chromosome condensation in the nucleus [ 20 , 21 , 22 ]; these results have not been independently verified. Overall, there was no confirmed evidence of MMWs causing genotoxic damage in epithelial and skin cells.

Three studies from an Indian research group have examined indicators of DNA damage and reactive oxygen species (ROS) production in rats exposed in vivo to MMWs. The studies reported DNA strand breaks based on evidence from comet assays [ 23 , 24 ] and changes in enzymes that control the build-up of ROS [ 24 ]. Kumar et al. also reported an increase in ROS production [ 25 ]. All the studies from this research group had low animal numbers (six animals exposed) and their results have not been independently replicated. An in vitro study that investigated ROS production in yeast cultures reported an increase in free radicals exposed to high-level but not low-level MMWs [ 26 ].

Other studies have looked at the effect of low-level MMWs on DNA in a range of different ways. Two studies reported that MMWs induce colicin synthesis and prophage induction in bacterial cells, both of which are suggested as indicative of DNA damage [ 27 , 28 ]. Another study suggested that DNA exposed to MMWs undergoes polymerase chain reaction synthesis differently than unexposed DNA [ 29 ], although no statistical analysis was presented. Hintzsche et al. reported statistically significant occurrence of spindle disturbance in hybrid cells exposed to MMWs [ 30 ]. Zeni et al. found no evidence of DNA damage or alteration of cell cycle kinetics in blood cells exposed to MMWs [ 31 ]. Last, two studies from a Russian research group examined the protective effects of MMWs where mouse blood leukocytes were pre-exposed to low-level MMWs and then to X-rays [ 32 , 33 ]. The studies reported that there was statistically significant less DNA damage in the leucocytes that were pre-exposed to MMWs than those exposed to X-rays alone. Overall, these studies had no independent replication.

Cell proliferation

A number of studies have examined the effects of low-level MMWs on cell proliferation and they have used a variety of cellular models and methods of investigation. Studies have exposed bacterial cells to low-level MMWs alone or in conjunction with other agents. Two early studies reported changes in the growth rate of E. coli cultures exposed to low-level MMWs; however, both of these studies were preliminary in nature without appropriate dosimetry or statistical analysis [ 34 , 35 ]. Two studies exposed E. coli cultures and one study exposed yeast cell cultures to MMWs alone, and before and after UVC exposure [ 36 , 37 , 38 ]. All three studies reported that MMWs alone had no significant effect on bacterial cell proliferation or survival. Rojavin et al., however, did report that when E. coli bacteria were exposed to MMWs after UVC sterilisation treatment, there was an increase in their survival rate [ 36 ]. The authors suggested this could be due to the MMW activation of bacterial DNA repair mechanisms. Other studies by an Armenian research group reported a reduction in E. coli cell growth when exposed to MMWs [ 39 , 40 , 41 , 42 , 43 , 44 , 45 ]. These studies reported that when E.coli cultures were exposed to MMWs in the presence of antibiotics, there was a greater reduction in the bacterial growth rate and an increase in the time between bacterial cell division compared with antibiotics exposure alone. Two of these studies investigated if these effects could be due to a reduction in the activity of the E. coli ATPase when exposed to MMWs. The studies reported exposure to MMWs in combination with particular antibiotics changed the concentration of H + and K + ions in the E.coli cells, which the authors linked to changes in ATPase activity [ 43 , 44 ]. Overall, the results from studies on cell proliferation of bacterial cells have been inconsistent with different research groups reporting conflicting results.

Studies have also examined how exposure to low-level MMWs could affect cell proliferation in yeast. Two early studies by a German research group reported changes in yeast cell growth [ 46 , 47 ]. However, another two independent studies did not report any changes in the growth rate of exposed yeast [ 48 , 49 ]. Furia et al. [ 48 ] noted that the Grundler and Keilmann studies [ 46 , 47 ] had a number of methodical issues, which may have skewed their results, such as poor exposure control and analysis of results. Another study exposed yeast to MMWs before and after UVC exposure and reported that MMWs did not change the rates of cell survival [ 37 ].

Studies have also examined the possible effect of low-level MMWs on tumour cells with some studies reporting a possible anti-proliferative effect. Chidichimo et al. reported a reduction in the growth of a variety of tumour cells exposed to MMWs; however, the results of the study did not support this conclusion [ 50 ]. An Italian research group published a number of studies investigating proliferation effects on human melanoma cell lines with conflicting results. Two of the studies reported reduced growth rate [ 51 , 52 ] and a third study showed no change in proliferation or in the cell cycle [ 53 ]. Beneduci et al. also reported changes in the morphology of MMW exposed cells; however, the authors did not present quantitative data for these reported changes [ 51 , 52 ]. In another study by the same Italian group, Beneduci et al. reported that exposure to low-level MMWs had a greater than 40% reduction in the number of viable erythromyeloid leukaemia cells compared with controls; however, there was no significant change in the number of dead cells [ 54 ]. More recently, Yaekashiwa et al. reported no statistically significant effect in proliferation or cellular activity in glioblastoma cells exposed to low-level MMWs [ 55 ].

Other studies did not report statistically significant effects on proliferation in chicken embryo cell cultures, rat nerve cells or human skin fibroblasts exposed to low-level MMWs [ 55 , 56 , 57 ].

Gene expression

Some studies have investigated whether low-level MMWs can influence gene expression. Le Queument et al. examined a multitude of genes using microarray analyses and reported transient expression changes in five of them. However, the authors concluded that these results were extremely minor, especially when compared with studies using microarrays to study known pollutants [ 58 ]. Studies by a French research group have examined the effect of MMWs on stress sensitive genes, stress sensitive gene promotors and chaperone proteins in human glial cell lines. In two studies, glial cells were exposed to low-level MMWs and there was no observed modification in the expression of stress sensitive gene promotors when compared with sham exposed cells [ 59 , 60 , 61 ]. Further, glial cells were examined for the expression of the chaperone protein clusterin (CLU) and heat shock protein HSP70. These proteins are activated in times of cellular stress to maintain protein functions and help with the repair process [ 60 ]. There was no observed modification in gene expression of the chaperone proteins. Other studies have examined the endoplasmic reticulum of glial cells exposed to MMWs [ 62 , 63 ]. The endoplasmic reticulum is the site of synthesis and folding of secreted proteins and has been shown to be sensitive to environmental insults [ 62 ]. The authors reported that there was no elevation in mRNA expression levels of endoplasmic reticulum specific chaperone proteins. Studies of stress sensitive genes in glial cells have consistently shown no modification due to low-level MMW exposure [ 59 , 60 , 61 , 62 , 63 ].

Belyaev and co-authors have studied a possible resonance effect of low-level MMWs primarily on Escherichia Coli (E. coli) cells and cultures. The Belyaev research group reported that the resonance effect of MMWs can change the conformation state of chromosomal DNA complexes [ 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 ]; however, most of these experiments were not temperature controlled. This resonance effect was not supported by earlier experiments on a number of different cell types conducted by Gandhi et al. and Bush et al. [ 75 , 76 ].

The results of Belyaev and co-workers have primarily been based on evidence from the anomalous viscosity time dependence (AVTD) method [ 77 ]. The research group argued that changes in the AVTD curve can indicate changes to the DNA conformation state and DNA-protein bonds. Belyaev and co-workers have reported in a number of studies that differences in the AVTD curve were dependent on several parameter including MMW characteristics (frequency, exposure level, and polarisation), cellular concentration and cell growth rate [ 69 , 71 , 72 , 73 , 74 ]. In some of the Belyaev studies E. coli were pre-exposed to X-rays, which was reported to change the AVTD curve; however, if the cells were then exposed to MMWs there was no longer a change in the AVTD curve [ 64 , 65 , 66 , 67 ]. The authors suggested that exposure to MMWs increased the rate of recovery in bacterial cells previously exposed to ionising radiation. The Belyaev group also used rat thymocytes in another study and they concluded that the results closely paralleled those found in E. coli cells [ 67 ]. The studies on the DNA conformation state change relied heavily on the AVTD method that has only been used by the Balyaev group and has not been independently validated [ 78 ].

Cell signalling and electrical activity

Studies examining effects of low-level MMWs on cell signalling have mainly involved MMW exposure to nervous system tissue of various animals. An in vivo study on rats recorded extracellular background electrical spike activity from neurons in the supraoptic nucleus of the hypothalamus after MMW exposure [ 79 ]. The study reported that there were changes in inter-spike interval and spike activity in the cells of exposed animals when compared with controls. There was also a mixture of significant shifts in neuron population proportions and spike frequency. The effect on the regularity of neuron spike activity was greater at higher frequencies. An in vitro study on rat cortical tissue slices reported that neuron firing rates decreased in half of the samples exposed to low-level MMWs [ 80 ]. The width of the signals was also decreased but all effects were short lived. The observed changes were not consistent between the two studies, but this could be a consequence of different brain regions being studied.

In vitro experiments by a Japanese research group conducted on crayfish exposed the dissected optical components and brain to MMWs [ 81 , 82 ]. Munemori and Ikeda reported that there was no significant change in the inter-spike intervals or amplitude of spontaneous discharges [ 81 ]. However, there was a change in the distribution of inter-spike intervals where the initial standard deviation decreased and then restored in a short time to a rhythm comparable to the control. A follow-up study on the same tissues and a wide range of exposure levels (many above the ICNIRP limits) reported similar results with the distribution of spike intervals decreasing with increasing exposure level [ 82 ]. These results on action potentials in crayfish tissue have not been independently investigated.

Mixed results were reported in experiments conducted by a US research group on sciatic frog nerve preparations. These studies applied electrical stimulation to the nerve and examined the effect of MMWs on the compound action potentials (CAPs) conductivity through the neurological tissue fibre. Pakhomov et al. found a reduction in CAP latency accompanied by an amplitude increase for MMWs above the ICNIRP limits but not for low-level MMWs [ 83 ]. However, in two follow-up studies, Pakhomov et al. reported that the attenuation in amplitude of test CAPs caused by high-rate stimulus was significantly reduced to the same magnitude at various MMW exposure levels [ 84 , 85 ]. In all of these studies, the observed effect on the CAPs was temporal and reversible, but there were implications of a frequency specific resonance interaction with the nervous tissue. These results on action potentials in frog sciatic nerves have not been investigated by others.

Other common experimental systems involved low-level MMW exposure to isolated ganglia of leeches. Pikov and Siegel reported that there was a decrease in the firing rate in one of the tested neurons and, through the measurement of input resistance in an inserted electrode, there was a transient dose-dependent change in membrane permeability [ 86 ]. However, Romanenko et al. found that low-level MMWs did not cause suppression of neuron firing rate [ 87 ]. Further experiments by Romanenko et al. reported that MMWs at the ICNIRP public exposure limit and above reported similar action potential firing rate suppression [ 88 ]. Significant differences were reported between MMW effects and effects due to an equivalent rise in temperature caused by heating the bathing solution by conventional means.

Membrane effects

Studies examining membrane interactions with low-level MMWs have all been conducted at frequencies above 40 GHz in in vitro experiments. A number of studies investigated membrane phase transitions involving exposure to a range of phospholipid vesicles prepared to mimic biological cell membranes. One group of studies by an Italian research group reported effects on membrane hydration dynamics and phase transition [ 89 , 90 , 91 ]. Observations included transition delays from the gel to liquid phase or vice versa when compared with sham exposures maintained at the same temperature; the effect was reversed after exposure. These reported changes remain unconfirmed by independent groups.

A number of studies investigated membrane permeability. One study focussed on Ca 2+ activated K + channels on the membrane surface of cultured kidney cells of African Green Marmosets [ 92 ]. The study reported modifications to the Hill coefficient and apparent affinity of the Ca 2+ by the K + channels. Another study reported that the effectiveness of a chemical to supress membrane permeability in the gap junction was transiently reduced when the cells were exposed to MMWs [ 93 , 94 ]. Two studies by one research group reported increases in the movement of molecules into skin cells during MMW exposure and suggested this indicates increased cell membrane permeability [ 21 , 91 ]. Permeability changes based on membrane pressure differences were also investigated in relation to phospholipid organisation [ 95 ]. Although there was no evidence of effects on phospholipid organisation on exposed model membranes, the authors reported a measurable difference in membrane pressure at low exposure levels. Another study reported neuron shrinkage and dehydration of brain tissues [ 96 ]. The study reported this was due to influences of low-level MMWs on the cellular bathing medium and intracellular water. Further, the authors suggested this influence of MMWs may have led to formation of unknown messengers, which are able to modulate brain cell hydration. A study using an artificial axon system consisting of a network of cells containing aqueous phospholipid vesicles reported permeability changes with exposure to MMWs by measuring K + efflux [ 97 ]. In this case, the authors emphasised limitations in applying this model to processes within a living organism. The varied effects of low-level MMWs on membrane permeability lack replication.

Other studies have examined the shape or size of vesicles to determine possible effects on membrane permeability. Ramundo-Orlando et al., reported effects on the shape of giant unilamellar vesicles (GUVs), specifically elongation, attributed to permeability changes [ 98 ]. However, another study reported that only smaller diameter vesicles demonstrated a statistically significant change when exposed to MMWs [ 99 ]. A study by Cosentino et al. examined the effect of MMWs on the size distributions of both large unilamellar vesicles (LUVs) and GUVs in in vitro preparations [ 100 ]. It was reported that size distribution was only affected when the vesicles were under osmotic stress, resulting in a statistically significant reduction in their size. In this case, the effect was attributed to dehydration as a result of membrane permeability changes. There is, generally, lack of replication on physical changes to phospholipid vesicles due to low-level MMWs.

Studies on E. coli and E. hirae cultures have reported resonance effects on membrane proteins and phospholipid constituents or within the media suspension [ 39 , 40 , 41 , 42 ]. These studies observed cell proliferation effects such as changes to cell growth rate, viability and lag phase duration. These effects were reported to be more pronounced at specific MMW frequencies. The authors suggested this could be due to a resonance effect on the cell membrane or the suspension medium. Torgomyan et al. and Hovnanyan et al. reported similar changes to proliferation that they attributed to changes in membrane permeability from MMW exposure [ 43 , 45 ]. These experiments were all conducted by an Armenian research group and have not been replicated by others.

Other effects

A number of studies have reported on the experimental results of other effects. Reproductive effects were examined in three studies on mice, rats and human spermatozoa. An in vivo study on mice exposed to low-level MMWs reported that spermatogonial cells had significantly more metaphase translocation disturbances than controls and an increased number of cells with unpaired chromosomes [ 101 ]. Another in vivo study on rats reported increased morphological abnormalities to spermatozoa following exposure, however, there was no statistical analysis presented [ 102 ]. Conversely, an in vitro study on human spermatozoa reported that there was an increase in motility after a short time of exposure to MMWs with no changes in membrane integrity and no generation of apoptosis [ 103 ]. All three of these studies looked at different effects on spermatozoa making it difficult to make an overall conclusion. A further two studies exposed rats to MMWs and examined their sperm for indicators of ROS production. One study reported both increases and decreases in enzymes that control the build-up of ROS [ 104 ]. The other study reported a decrease in the activity of histone kinase and an increase in ROS [ 105 ]. Both studies had low animal numbers (six animals exposed) and these results have not been independently replicated.

Immune function was also examined in a limited number of studies focussing on the effects of low-level MMWs on antigens and antibody systems. Three studies by a Russian research group that exposed neutrophils to MMWs reported frequency dependant changes in ROS production [ 106 , 107 , 108 ]. Another study reported a statistically significant decrease in antigen binding to antibodies when exposed to MMWs [ 109 ]; the study also reported that exposure decreased the stability of previously formed antigen–antibody complexes.

The effect on fatty acid composition in mice exposed to MMWs has been examined by a Russian research group using a number of experimental methods [ 110 , 111 , 112 ]. One study that exposed mice afflicted with an inflammatory condition to low-level MMWs reported no change in the fatty acid concentrations in the blood plasma. However, there was a significant increase in the omega-3 and omega-6 polyunsaturated fatty acid content of the thymus [ 110 ]. Another study exposed tumour-bearing mice and reported that monounsaturated fatty acids decreased and polyunsaturated fatty acids increased in both the thymus and tumour tissue. These changes resulted in fatty acid composition of the thymus tissue more closely resembling that of the healthy control animals [ 111 ]. The authors also examined the effect of exposure to X-rays of healthy mice, which was reported to reduce the total weight of the thymus. However, when the thymus was exposed to MMWs before or after exposure to X-rays, the fatty acid content was restored and was no longer significantly different from controls [ 112 ]. Overall, the authors reported a potential protective effect of MMWs on the recovery of fatty acids, however, all the results came from the same research group with a lack of replication from others.

Physiological effects were examined by a study conducted on mice exposed to WWMs to assess the safety of police radar [ 113 ]. The authors reported no statistically significant changes in the physiological parameters tested, which included body mass and temperature, peripheral blood and the mass and cellular composition, and number of cells in several important organs. Another study exposing human volunteers to low-level MMWs specifically examined cardiovascular function of exposed and sham exposed groups by electrocardiogram (ECG) and atrioventricular conduction velocity derivation [ 114 ]. This study reported that there were no significant differences in the physiological indicators assessed in test subjects.

Other individual studies have looked at various other effects. An early study reported differences in the attenuation of MMWs at specific frequencies in healthy and tumour cells [ 115 ]. Another early study reported no effect in the morphology of BHK-21/C13 cell cultures when exposed to low-level MMWs; the study did report morphological changes at higher levels, which were related to heating [ 116 ]. One study examined whether low-level MMWs induced cancer promotion in leukaemia and Lewis tumour cell grafted mice. The study reported no statistically significant growth promotion in either of the grafted cancer cell types [ 117 ]. Another study looked at the activity of gamma-glutamyl transpeptidase enzyme in rats after treatment with hydrocortisone and exposure to MMWs [ 118 ]. The study reported no effects at exposures below the ICNIRP limit, however, at levels above authors reported a range of effects. Another study exposed saline liquid solutions to continuous low and high level MMWs and reported temperature oscillations within the liquid medium but lacked a statistical analysis [ 119 ]. Another study reported that low-level MMWs decrease the mobility of the protozoa S. ambiguum offspring [ 120 ]. None of the reported effects in all of these other studies have been investigated elsewhere.

Epidemiological studies

There are no epidemiological studies that have directly investigated 5 G and potential health effects. There are however epidemiological studies that have looked at occupational exposure to radar, which could potentially include the frequency range from 6 to 300 GHz. Epidemiological studies on radar were included as they represent occupational exposure below the ICNIRP guidelines. The review included 31 epidemiological studies (8 cohort, 13 case-control, 9 cross-sectional and 1 meta-analysis) that investigated exposure to radar and various health outcomes including cancer at different sites, effects on reproduction and other diseases. The risk estimates as well as limitations of the epidemiological studies are shown in Table  7 .

Three large cohort studies investigated mortality in military personnel with potential exposure to MMWs from radar. Studies reporting on over 40-year follow-up of US navy veterans of the Korean War found that radar exposure had little effect on all-cause or cancer mortality with the second study reporting risk estimates below unity [ 121 , 122 ]. Similarly, in a 40-year follow-up of Belgian military radar operators, there was no statistically significant increase in all-cause mortality [ 123 , 124 ]; the study did, however, find a small increase in cancer mortality. More recently in a 25-year follow-up of military personnel who served in the French Navy, there was no increase in all-cause or cancer mortality for personnel exposed to radar [ 125 ]. The main limitation in the cohort studies was the lack of individual levels of RF exposure with most studies based on job-title. Comparisons were made between occupations with presumed high exposure to RF fields and other occupations with presumed lower exposure. This type of non-differential misclassification in dichotomous exposure assessment is associated mostly with an effect measure biased towards a null effect if there is a true effect of RF fields. If there is no true effect of RF fields, non-differential exposure misclassification will not bias the effect estimate (which will be close to the null value, but may vary because of random error). The military personnel in these studies were compared with the general population and this ‘healthy worker effect’ presents possible bias since military personnel are on average in better health than the general population; the healthy worker effect tends to underestimate the risk. The cohort studies also lacked information on possible confounding factors including other occupational exposures such as chemicals and lifestyle factors such as smoking.

Several epidemiological studies have specifically investigated radar exposure and testicular cancer. In a case-control study where most of the subjects were selected from military hospitals in Washington DC, USA, Hayes et al. found no increased risk between exposure to radar and testicular cancer [ 126 ]; exposure to radar was self-reported and thus subject to misclassification. In this study, the misclassification was likely non-differential, biasing the result towards the null. Davis and Mostofi reported a cluster of testicular cancer within a small cohort of 340 police officers in Washington State (USA) where the cases routinely used handheld traffic radar guns [ 127 ]; however, exposure was not assessed for the full cohort, which may have overestimated the risk. In a population-based case-control study conducted in Sweden, Hardell et al. did not find a statistically significant association between radar work and testicular cancer; however, the result was based on only five radar workers questioning the validity of this result [ 128 ]. In a larger population-based case control study in Germany, Baumgardt-Elms et al. also reported no association between working near radar units (both self-reported and expert assessed) and testicular cancer [ 129 ]; a limitation of this study was the low participation of identified controls (57%), however, there was no difference compared with the characteristics of the cases so selection bias was unlikely. In the cohort study of US navy veterans previously mentioned exposure to radar was not associated with testicular cancer [ 122 ]; the limitations of this cohort study mentioned earlier may have underestimated the risk. Finally, in a hospital-based case-control study in France, radar workers were also not associated with risk of testicular cancer [ 130 ]; a limitation was the low participation of controls (37%) with a difference in education level between participating and non-participating controls, which may have underestimated this result.

A limited number of studies have investigated radar exposure and brain cancer. In a nested case-control study within a cohort of male US Air Force personnel, Grayson reported a small association between brain cancer and RF exposure, which included radar [ 131 ]; no potential confounders were included in the analysis, which may have overestimated the result. However, in a case-control study of personnel in the Brazilian Navy, Santana et al. reported no association between naval occupations likely to be exposed to radar and brain cancer [ 132 ]; the small number of cases and lack of diagnosis confirmation may have biased the results towards the null. All of the cohort studies on military personnel previously mentioned also examined brain cancer mortality and found no association with exposure to radar [ 122 , 124 , 125 ].

A limited number of studies have investigated radar exposure and ocular cancer. Holly et al. in a population-based case-control study in the US reported an association between self-reported exposure to radar or microwaves and uveal melanoma [ 133 ]; the study investigated many different exposures and the result is prone to multiple testing. In another case-control study, which used both hospital and population controls, Stang et al. did not find an association between self-reported exposure to radar and uveal melanoma [ 134 ]; a high non-response in the population controls (52%) and exposure misclassification may have underestimated this result. The cohort studies of the Belgian military and French navy also found no association between exposure to radar and ocular cancer [ 124 , 125 ].

A few other studies have examined the potential association between radar and other cancers. In a hospital-based case-control study in Italy, La Vecchia investigated 14 occupational agents and risk of bladder cancer and found no association with radar, although no risk estimate was reported [ 135 ]; non-differential self-reporting of exposure may have underestimated this finding if there is a true effect. Finkelstein found an increased risk for melanoma in a large cohort of Ontario police officers exposed to traffic radar and followed for 31 years [ 136 ]; there was significant loss to follow up which may have biased this result in either direction. Finkelstein found no statistically significant associations with other types of cancer and the study reported a statistically significant risk estimate just below unity for all cancers, which is reflective of the healthy worker effect [ 136 ]. In a large population-based case-control study in France, Fabbro-Peray et al. investigated a large number of occupational and environmental risk factors in relation to non-Hodgkin lymphoma and found no association with radar operators based on job-title; however, the result was based on a small number of radar operators [ 137 ]. The cohort studies on military personnel did not find statistically significant associations between exposure to radar and other cancers [ 122 , 124 , 125 ].

Variani et al. conducted a recent systematic review and meta-analysis investigating occupational exposure to radar and cancer risk [ 138 ]. The meta-analysis included three cohort studies [ 122 , 124 , 125 ] and three case-control studies [ 129 , 130 , 131 ] for a total sample size of 53,000 subjects. The meta-analysis reported a decrease in cancer risk for workers exposed to radar but noted the small number of studies included with significant heterogeneity between the studies.

Apart from cancer, a number of epidemiological studies have investigated radar exposure and reproductive outcomes. Two early studies on military personnel in the US [ 139 ] and Denmark [ 140 ] reported differences in semen parameters between personnel using radar and personnel on other duty assignments; these studies included only volunteers with potential fertility concerns and are prone to bias. A further volunteer study on US military personnel did not find a difference in semen parameters in a similar comparison [ 141 ]; in general these type of cross-sectional investigations on volunteers provide limited evidence on possible risk. In a case-control study of personnel in the French military, Velez de la Calle et al. reported no association between exposure to radar and male infertility [ 142 ]; non-differential self-reporting of exposure may have underestimated this finding if there is a true effect. In two separate cross-sectional studies of personnel in the Norwegian navy, Baste et al. and Møllerløkken et al. reported an association between exposure to radar and male infertility, but there has been no follow up cohort or case control studies to confirm these results [ 143 , 144 ].

Again considering reproduction, a number of studies investigated pregnancy and offspring outcomes. In a population-based case-control study conducted in the US and Canada, De Roos et al. found no statistically significant association between parental occupational exposure to radar and neuroblastoma in offspring; however, the result was based on a small number of cases and controls exposed to radar [ 145 ]. In another cross-sectional study of the Norwegian navy, Mageroy et al. reported a higher risk of congenital anomalies in the offspring of personnel who were exposed to radar; the study found positive associations with a large number of other chemical and physical exposures, but the study involved multiple comparisons so is prone to over-interpretation [ 146 ]. Finally, a number of pregnancy outcomes were investigated in a cohort study of Norwegian navy personnel enlisted between 1950 and 2004 [ 147 ]. The study reported an increase in perinatal mortality for parental service aboard fast patrol boats during a short period (3 months); exposure to radar was one of many possible exposures when serving on fast patrol boats and the result is prone to multiple testing. No associations were found between long-term exposure and any pregnancy outcomes.

There is limited research investigating exposure to radar and other diseases. In a large case-control study of US military veterans investigating a range of risk factors and amyotrophic lateral sclerosis, Beard et al. did not find a statistically significant association with radar [ 148 ]; the study reported a likely under-ascertainment of non-exposed cases, which may have biased the result away from the null. The cohort studies on military personnel did not find statistically significant associations between exposure to radar and other diseases [ 122 , 124 , 125 ].

A number of observational studies have investigated outcomes measured on volunteers in the laboratory. They are categorised as epidemiological studies because exposure to radar was not based on provocation. These studies investigated genotoxicity [ 149 ], oxidative stress [ 149 ], cognitive effects [ 150 ] and endocrine function [ 151 ]; the studies generally reported positive associations with radar. These volunteer studies did not sample from a defined population and are prone to bias [ 152 ].

The experimental studies investigating exposure to MMWs at levels below the ICNIRP occupational limits have looked at a variety of biological effects. Genotoxicity was mainly examined by using comet assays of exposed cells. This approach has consistently found no evidence of DNA damage in skin cells in well-designed studies. However, animal studies conducted by one research group reported DNA strand breaks and changes in enzymes that control the build-up of ROS, noting that these studies had low animal numbers (six animals exposed); these results have not been independently replicated. Studies have also investigated other indications of genotoxicity including chromosome aberrations, micro-nucleation and spindle disturbances. The methods used to investigate these indicators have generally been rigorous; however, the studies have reported contradictory results. Two studies by a Russian research group have also reported indicators of DNA damage in bacteria, however, these results have not been verified by other investigators.

The studies of the effect of MMWs on cell proliferation primarily focused on bacteria, yeast cells and tumour cells. Studies of bacteria were mainly from an Armenian research group that reported a reduction in the bacterial growth rate of exposed E. coli cells at different MMW frequencies; however, the studies suffered from inadequate dosimetry and temperature control and heating due to high RF energy deposition may have contributed to the results. Other authors have reported no effect of MMWs on E. coli cell growth rate. The results on cell proliferation of yeast exposed to MMWs were also contradictory. An Italian research group that has conducted the majority of the studies on tumour cells reported either a reduction or no change in the proliferation of exposed cells; however, these studies also suffered from inadequate dosimetry and temperature control.

The studies on gene expression mainly examined two different indicators, expression of stress sensitive genes and chaperone proteins and the occurrence of a resonance effect in cells to explain DNA conformation state changes. Most studies reported no effect of low-level MMWs on the expression of stress sensitive genes or chaperone proteins using a range of experimental methods to confirm these results; noting that these studies did not use blinding so experimental bias cannot be excluded from the results. A number of studies from a Russian research group reported a resonance effect of MMWs, which they propose can change the conformation state of chromosomal DNA complexes. Their results relied heavily on the AVTD method for testing changes in the DNA conformation state, however, the biological relevance of results obtained through the AVTD method has not been independently validated.

Studies on cell signalling and electrical activity reported a range of different outcomes including increases or decreases in signal amplitude and changes in signal rhythm, with no consistent effect noting the lack of blinding in most of the studies. Further, temperature contributions could not be eliminated from the studies and in some cases thermal interactions by conventional heating were studied and found to differ from the MMW effects. The results from some studies were based on small sample sizes, some being confined to a single specimen, or by observed effects only occurring in a small number of the samples tested. Overall, the reported electrical activity effects could not be dismissed as being within normal variability. This is indicated by studies reporting the restoration of normal function within a short time during ongoing exposure. In this case there is no implication of an expected negative health outcome.

Studies on membrane effects examined changes in membrane properties and permeability. Some studies observed changes in transitions from liquid to gel phase or vice versa and the authors implied that MMWs influenced cell hydration, however the statistical methods used in these studies were not described so it is difficult to examine the validity of these results. Other studies observing membrane properties in artificial cell suspensions and dissected tissue reported changes in vesicle shape, reduced cell volume and morphological changes although most of these studies suffered from various methodological problems including poor temperature control and no blinding. Experiments on bacteria and yeast were conducted by the same research group reporting changes in membrane permeability, which was attributed to cell proliferation effects, however, the studies suffered from inadequate dosimetry and temperature control. Overall, although there were a variety of membrane bioeffects reported, these have not been independently replicated.

The limited number of studies on a number of other effects from exposure to MMWs below the ICNIRP limits generally reported little to no consistent effects. The single in vivo study on cancer promotion did not find an effect although the study did not include sham controls. Effects on reproduction were contradictory that may have been influenced by opposing objectives of examining adverse health effects or infertility treatment. Further, the only study on human sperm found no effects of low-level MMWs. The studies on reproduction suffered from inadequate dosimetry and temperature control, and since sperm is sensitive to temperature, the effect of heating due to high RF energy deposition may have contributed to the studies showing an effect. A number of studies from two research groups reported effects on ROS production in relation to reproduction and immune function; the in vivo studies had low animal numbers (six animals per exposure) and the in vitro studies generally had inadequate dosimetry and temperature control. Studies on fatty acid composition and physiological indicators did not generally show any effects; poor temperature control was also a problem in the majority of these studies. A number of other studies investigating various other biological effects reported mixed results.

Although a range of bioeffects have been reported in many of the experimental studies, the results were generally not independently reproduced. Approximately half of the studies were from just five laboratories and several studies represented a collaboration between one or more laboratories. The exposure characteristics varied considerably among the different studies with studies showing the highest effect size clustered around a PD of approximately 1 W/m 2 . The meta-analysis of the experimental studies in our companion paper [ 9 ] showed that there was no dose-response relationship between the exposure (either PD or SAR) and the effect size. In fact, studies with a higher exposure tended to show a lower effect size, which is counterfactual. Most of the studies showing a large effect size were conducted in the frequency range around 40–55 GHz, representing investigations into the use of MMWs for therapeutic purposes, rather than deleterious health consequences. Future experimental research would benefit from investigating bioeffects at the specific frequency range of the next stage of the 5 G network roll-out in the range 26–28 GHz. Mobile communications beyond the 5 G network plan to use frequencies higher than 30 GHz so research across the MMW band is relevant.

An investigation into the methods of the experimental studies showed that the majority of studies were lacking in a number of quality criteria including proper attention to dosimetry, incorporating positive controls, using blind evaluation or accurately measuring or controlling the temperature of the biological system being tested. Our meta-analysis showed that the bulk of the studies had a quality score lower than 2 out of a possible 5, with only one study achieving a maximum quality score of 5 [ 9 ]. The meta-analysis further showed that studies with a low quality score were more likely to show a greater effect. Future research should pay careful attention to the experimental design to reduce possible sources of artefact.

The experimental studies included in this review reported PDs below the ICNIRP exposure limits. Many of the authors suggested that the resulting biological effects may be related to non-thermal mechanisms. However, as is shown in our meta-analysis, data from these studies should be treated with caution because the estimated SAR values in many of the studies were much higher than the ICNIRP SAR limits [ 9 ]. SAR values much higher than the ICNIRP guidelines are certainly capable of producing significant temperature rise and are far beyond the levels expected for 5 G telecommunication devices [ 1 ]. Future research into the low-level effects of MMWs should pay particular attention to appropriate temperature control in order to avoid possible heating effects.

Although a systematic review of experimental studies was not conducted, this paper presents a critical appraisal of study design and quality of all available studies into the bioeffects of low level MMWs. The conclusions from the review of experimental studies are supported by a meta-analysis in our companion paper [ 9 ]. Given the low-quality methods of the majority of the experimental studies we infer that a systematic review of different bioeffects is not possible at present. Our review includes recommendations for future experimental research. A search of the available literature showed a further 44 non-English papers that were not included in our review. Although the non-English papers may have some important results it is noted that the majority are from research groups that have published English papers that are included in our review.

The epidemiological studies on MMW exposure from radar that has a similar frequency range to that of 5 G and exposure levels below the ICNIRP occupational limits in most situations, provided little evidence of an association with any adverse health effects. Only a small number of studies reported positive associations with various methodological issues such as risk of bias, confounding and multiple testing questioning the result. The three large cohort studies of military personnel exposed to radar in particular did not generally show an association with cancer or other diseases. A key concern across all the epidemiological studies was the quality of exposure assessment. Various challenges such as variability in complex occupational environments that also include other co-exposures, retrospective estimation of exposure and an appropriate exposure metric remain central in studies of this nature [ 153 ]. Exposure in most of the epidemiological studies was self-reported or based on job-title, which may not necessarily be an adequate proxy for exposure to RF fields above 6 GHz. Some studies improved on exposure assessment by using expert assessment and job-exposure matrices, however, the possibility of exposure misclassification is not eliminated. Another limitation in many of the studies was the poor assessment of possible confounding including other occupational exposures and lifestyle factors. It should also be noted that close proximity to certain very powerful radar units could have exceeded the ICNIRP occupational limits, therefore the reported effects especially related to reproductive outcomes could potentially be related to heating.

Given that wireless communications have only recently started to use RF frequencies above 6 GHz there are no epidemiological studies investigating 5 G directly as yet. Some previous epidemiological studies have reported a possible weak association between mobile phone use (from older networks using frequencies below 6 GHz) and brain cancer [ 11 ]. However, methodological limitations in these studies prevent conclusions of causality being drawn from the observations [ 152 ]. Recent investigations have not shown an increase in the incidence of brain cancer in the population that can be attributed to mobile phone use [ 154 , 155 ]. Future epidemiological research should continue to monitor long-term health effects in the population related to wireless telecommunications.

The review of experimental studies provided no confirmed evidence that low-level MMWs are associated with biological effects relevant to human health. Many of the studies reporting effects came from the same research groups and the results have not been independently reproduced. The majority of the studies employed low quality methods of exposure assessment and control so the possibility of experimental artefact cannot be excluded. Further, many of the effects reported may have been related to heating from high RF energy deposition so the assertion of a ‘low-level’ effect is questionable in many of the studies. Future studies into the low-level effects of MMWs should improve the experimental design with particular attention to dosimetry and temperature control. The results from epidemiological studies presented little evidence of an association between low-level MMWs and any adverse health effects. Future epidemiological research would benefit from specific investigation on the impact of 5 G and future telecommunication technologies.

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This work was supported by the Australian Government’s Electromagnetic Energy Program. This work was also partly supported by National Health and Medical Research Council grant no. 1042464. 

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Karipidis, K., Mate, R., Urban, D. et al. 5G mobile networks and health—a state-of-the-science review of the research into low-level RF fields above 6 GHz. J Expo Sci Environ Epidemiol 31 , 585–605 (2021). https://doi.org/10.1038/s41370-021-00297-6

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• Research areas in 5G technology

Research areas in 5G Technology

We are currently on the cusp of 5G rollout. As industry experts predict , 5G deployments will gain momentum, and the accessibility of 5G devices will grow in 2020 and beyond. But as the general public waits for mass-market 5G devices, our understanding of this new technology is continuing to develop. Public and private organizations are exploring several research areas in 5G technology, helping to create more awareness of breakthroughs in this technology, its potential applications and implications, and the challenges surrounding it. 

What is especially clear at this point is that 5G technology offers a transformative experience for mobile communications around the globe. Its benefits, which include higher data rates, faster connectivity, and potentially lower power consumption, promise to benefit industry, professional users, casual consumers, and everyone in between. As this article highlights, researchers have not yet solved or surmounted all of the challenges and obstacles surrounding the wide scale deployment of 5G technology. But the potential impact that it will have on the entire matrix of how we communicate is limited only by the imagination of the experts currently at its frontier. 

New developments and applications in 5G technologies

Much of the transformative impact of 5G stems from the higher data transmission speeds and lower latency that this fifth generation of cellular technology enables. Currently, when you click on a link or start streaming a video, the lag time between your request to the network and its delivery to your device is about twenty milliseconds. 

That may not seem like a long time. But for the expert mobile robotics surgeon, that lag might be the difference between a successful or failed procedure. With 5G, latency can be as low as one millisecond. 

5G will greatly increase bandwidth capacity and transmission speeds. Wireless carriers like Verizon and AT&T have recorded speeds of one gigabyte per second. That’s anywhere from ten to one hundred times faster than an average cellular connection and even faster than a fiber-optic cable connection. Such speeds offer exciting possibilities for new developments and applications in numerous industries and economic sectors.

E-health services

For example, 5G speeds allow telemedicine services to enhance their doctor-patient relationships by decreasing troublesome lag times in calls. This helps patients return to the experience of intimacy they are used to from in-person meetings with health-care professionals. 

As 5G technology continues to advance its deployment, telemedicine specialists find that they can live anywhere in the world, be licensed in numerous states, and have faster access to cloud data storage and retrieval. This is especially important during the COVID-19 pandemic , which is spurring new developments in telemedicine as a delivery platform for medical services. 

Energy infrastructure

In addition to transforming e-health services, the speed and reliability of 5G network connectivity can improve the infrastructure of America’s energy sector with smart power grids. Such grids bring automation to the legacy power arrangement, optimizing the storage and delivery of energy. With smart power grids, the energy sector can more effectively manage power consumption and distribution based on need and integrate off-grid energy sources such as windmills and solar panels.

Another specific area to see increased advancement due to 5G technology is artificial intelligence (AI). One of the main barriers to successful integration of AI is processing speeds. With 5G, data transfer speeds are ten times faster than those possible with 4G. This makes it possible to receive and analyze information much more efficiently. And it puts AI on a faster track in numerous industries in both urban and rural settings. 

In rural settings, for example, 5G is helping improve cattle farming efficiency . By placing sensors on cows, farmers capture data that AI and machine learning can process to predict when cows are likely to give birth. This helps both farmers and veterinarians better predict and prepare for cow pregnancies.

However, it’s heavily populated cities across the country that are likely to witness the most change as mobile networks create access to heretofore unexperienced connectivity. 

Smart cities

Increased connectivity is key to the emergence of smart cities . These cities conceive of improving the living standards of residents by increasing the connectivity infrastructure of the city. This affects numerous aspects of city life, from traffic management and safety and security to governance, education, and more. 

Smart cities become “smarter” when services and applications become remotely accessible. Hence, innovative smartphone applications are key to smart city infrastructure. But the potential of these applications is seriously limited in cities with spotty connectivity and wide variations in data transmission speed. This is why 5G technology is crucial to continued developments in smart cities.

Other applications

Many other industries and economic sectors will benefit from 5G. Additional examples include automotive communication, smart retail and manufacturing. 

Wave spectrum challenges with 5G

While the potential applications of 5G technology are exciting, realizing the technology’s potential is not without its challenges. Notably, 5G global upgrades and changes are producing wave spectrum challenges.

A number of companies, such as Samsung, Huawei Technologies, ZTE Corporation, Nokia Networks, Qualcomm, Verizon, AT&T, and Cisco Systems are competing to make 5G technology available across the globe. But while in competition with each other, they all share the same goal and face the same dilemma.

Common goal

The goal for 5G is to provide the requisite bandwidth to every user with a device capable of higher data rates. Networks can provide this bandwidth by using a frequency spectrum above six gigahertz . 

Though the military has already been using frequencies above six gigahertz, commercial consumer-based networks are now doing so for the first time. All over the globe, researchers are exploring the new possibilities of spectrum and frequency channels for 5G communications. And they are focusing on the frequency range between twenty-five and eighty-six gigahertz.

Common dilemma

While researchers see great potential with a high-frequency version of 5G, it comes with a key challenge. It is very short range. Objects such as trees and buildings cause significant signal obstruction, necessitating numerous cell towers to avoid signal path loss. 

However, multiple-input, multiple-output (MIMO) technology is proving to be an effective technique for expanding the capacity of 5G connectivity and addressing signal path challenges. Researchers are keying into MIMO deployment due to its design simplicity and multiple offered features. 

A massive MIMO network can provide service to an increased multiplicity of mobile devices in a condensed area at a single frequency simultaneously. And by facilitating a greater number of antennas, a massive MIMO network is more resistant to signal interference and jamming.

Even with MIMO technology, however, line of sight will still be important for high-frequency 5G. Base stations on top of most buildings are likely to remain a necessity. As such, a complete 5G rollout is potentially still years away. 

Current solutions and the way forward

In the interim, telecommunication providers have come up with an alternative to high-frequency 5G— “midband spectrum.” This is what T-Mobile uses. But this compromise does not offer significant performance benefits in comparison to 4G and thus is unlikely to satisfy user expectations. 

Despite the frequency challenges currently surrounding 5G, it is important to keep in mind that there is a common evolution with new technological developments. Initial efforts to develop new technology are often complex and proprietary at the outset. But over time, innovation and advancements provide a clear, unified pathway forward.

This is the path that 5G is bound to follow. Currently, however, MIMO technological advancements notwithstanding, 5G rollout is still in its early, complex phase.

Battery life and energy storage for 5G equipment

For users to enjoy the full potential of 5G technology, longer battery life and better energy storage is essential. So this is what the industry is aiming for.

Currently, researchers are looking to lithium battery technology to boost battery life and optimize 5G equipment for user expectations. However, the verdict is mixed when it comes to the utility of lithium batteries in a 5G world. 

Questions about battery demands and performance

In theory, 5G smartphones will be less taxed than current smartphones. This is because a 5G network with local 5G base stations will dramatically increase computation speeds and enable the transfer of the bulk of computation from your smartphone to the cloud. This means less battery usage for daily tasks and longer life for your battery. Or does it?

A competing theory focuses on the 5G phones themselves. Unlike 4G chips, the chips that power 5G phones are incredibly draining to lithium batteries. 

Early experiments indicate that the state-of-the-art radio frequency switches running in smartphones are continually jumping from 3G to 4G to Wi-Fi. As a smartphone stays connected to these different sources, its battery drains faster.

The present limited infrastructure of 5G exacerbates this problem. Current 5G smartphones need to maintain a connection to multiple networks in order to ensure consistent phone call, text message, and data delivery. And this multiplicity of connections contributes to battery drain.

Until the technology improves and becomes more widely available, consumers are left with a choice: the regular draining expectations that come with 4G devices or access to the speeds and convenience of 5G Internet. 

Possibilities for improvement on the horizon

Fortunately, what can be expected with continuous 5G rollout is continuous improvements in battery performance. As 5G continues to expand across the globe, increasing the energy density and extending the lifetime of batteries will be vital. So market competition for problem-solving battery solutions promises to be fierce and drive innovation to meet user expectations. 

Additional research areas in 5G technology

While research in battery technology remains important, researchers are also focusing their attention on a number of other areas of concern. This research is likewise aimed at meeting user expectations and realizing the full potential of 5G technology as it gains more footing in public and private sectors. 

Small cell research

For example, researchers are focusing on small cells to meet the much higher data capacity demands of 5G networks. As mobile carriers look to densify their networks, small cell research is leading the way toward a solution.

Small cells are low-powered radio access points that take the place of traditional wireless transmission systems or base stations. By making use of low-power and short-range transmissions in small geographic areas, small cells are particularly well suited for the rollout of high-frequency 5G. As such, small cells are likely to appear by the hundreds of thousands across the United States as cellular companies work to improve mobile communication for their subscribers. The faster small cell technology advances, the sooner consumers will have specific 5G devices connected to 5G-only Internet. 

Security-oriented research

Security is also quickly becoming a major area of focus amid the push for a global 5G rollout. Earlier iterations of cellular technology were based primarily on hardware. When voice and text were routed to separate physical devices, each device managed its own network security. There was network security for voice calls, network security for short message system (SMS), and so forth.

5G moves away from this by making everything more software based. In theory, this makes things less secure, as there are now more ways to attack the network. Originally, 5G did have some security layers built in at the federal level. Under the Obama administration, legislation mandating clearly defined security at the network stage passed. However, the Trump administration is looking to replace these security layers with its own “national spectrum strategy.”

With uncertainty about existing safeguards, the cybersecurity protections available to citizens and governments amid 5G rollout is a matter of critical importance. This is creating a market for new cybersecurity research and solutions—solutions that will be key to safely and securely realizing the true value of 5G wireless technology going forward.

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• Published: 23 April 2021

Network slicing: a next generation 5G perspective

• Prashant Subedi 1 ,
• Abeer Alsadoon   ORCID: orcid.org/0000-0002-2309-3540 1 , 2 ,
• P. W. C. Prasad 1 ,
• Sabih Rehman   ORCID: orcid.org/0000-0001-7717-2773 3 ,
• Nabil Giweli 2 ,
• Muhammad Imran 4 &
• Samrah Arif 3  

EURASIP Journal on Wireless Communications and Networking volume  2021 , Article number:  102 ( 2021 ) Cite this article

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Fifth-generation (5G) wireless networks are projected to bring a major transformation to the current fourth-generation network to support the billions of devices that will be connected to the Internet. 5G networks will enable new and powerful capabilities to support high-speed data rates, better connectivity and system capacity that are critical in designing applications in virtual reality, augmented reality and mobile online gaming. The infrastructure of a network that can support stringent application requirements needs to be highly dynamic and flexible. Network slicing can provide these dynamic and flexible characteristics to a network architecture. Implementing network slicing in 5G requires domain modification of the preexisting network architecture. A network slicing architecture is proposed for an existing 5G network with the aim of enhancing network dynamics and flexibility to support modern network applications. To enable network slicing in a 5G network, we established the virtualisation of the underlying physical 5G infrastructure by utilising technological advancements, such as software-defined networking and network function virtualisation. These virtual networks can fulfil the requirement of multiple use cases as required by creating slices of these virtual networks. Thus, abstracting from the physical resources to create virtual networks and then applying network slicing on these virtual networks enable the 5G network to address the increased demands for high-speed communication.

1 Introduction

Over the recent years, the substantial increase in the use of handheld gadgets has resulted in a massive surge in the volume of mobile traffic across private and enterprise networks as well as across the global internet [ 1 ]. Virtual reality (VR) and augmented reality (AR), which are relatively new application/service types, have emerged and added to the mobile data traffic exponentially. This increased demand in traffic along with higher bandwidth requirements are reasons to upgrade the fourth-generation (4G) network architecture with the new fifth-generation (5G) network. The 5G network can provide high data rates and improved reliability with low delay and latency while supporting high mobility of users. However, the 5G network has several shortcomings that prevent the upgrade from achieving all the above mentioned characteristics [ 2 ]. Although hardware upgrades can be used to address these shortcomings, such upgrades can be expensive and are therefore not feasible. Recent technologies, such as software-defined networking (SDN) and network function virtualisation (NFV), have made addressing such issues possible without the need to upgrade the physical infrastructure [ 3 ]. Using these technologies also enhances network flexibility and scalability. SDN and NFV can be used as the key components in the architecture of the 5G network, and using these technologies allows the network to be separated into different slices, which can then be dedicated to different use cases, such as Internet of things (IoT), smartphones applications and intelligent vehicles. This feature of creating network slices that correspond to the demands of each service can be a major differentiating feature of the next generation 5G network. Concepts of SDN and NFV play an important role in the creation of network slices by allowing software abstraction and virtualisation of networks. Given the advanced nature of the applications and devices in use today, SDN and NFV allow for the management of network resources and services in a flexible and dynamic manner to meet the demands of today’s network [ 4 ]. This work on network slicing will help provide a better understanding of the 5G network architecture, network slicing architecture and the effectiveness of network slicing in terms of performance, resource utilisation and flexibility. In this article we provide a comprehensive taxonomy of a network slicing model that is used in the 5G network domain. This taxonomy is based on different factors, such as network nodes, slicing scope, slice isolation and slice management, which are the types of use cases served by the 5G network and enabler techniques, namely SDN and NVF. The key contribution of this work is threefold:

to introduce the network slicing concept, which includes areas of the 5G network in which slicing will be implemented

to understand different use cases that need to be served by the network slices to allow the understanding of different types of network slice requirements and

to showcase enabler techniques, which include understanding a range of techniques that will enable the process of network slicing in the 5G network architecture.

In conceiving the design of network slices architecture, different past and current systems can be compared and analysed based on the work conducted. In this article, we briefly outlined the 5G network nodes, network slicing use cases and the enabler techniques that establish a 5G Network Slicing Use Cases with Enabling Techniques (5G-NSUE) paradigm. Each major component required for network slicing was defined and discussed along with clear examples. This analysis and validation of the major entities of the current system will allow future researchers to easily recognise the components that can be reused and need improvement or different solutions and approaches.

The remainder of this paper is organised as follows: Sect.  2 introduces the concept of network slicing in a context of communication technology. Section  3 provides a discussion of previous work on network slicing in 5G network. Section  4 presents discussion related to the system components that are required for a network slicing model ED paradigm and describes them briefly. Section  5 discusses and illustrates how the classification can be used in a real-world scenario, in which the taxonomy is instantiated by classifying recent publications in this domain. In Sect.  7 a detailed discussion to validate the architecture and its application in various technologies has been discussed. Finally, Sect.  8 presents the conclusion.

2 Technology background

As the name suggests, network slicing involves creating the slices of a designated network. The key feature of this technology is that each created slice has different attributes, such as low latency, ultra-high bandwidth and mobile broadband. The advantage of these slices is that they can now be used to serve multiple different use cases according to need. For example, real-time streaming application requires a low-latency network slice, whereas streaming high-definition videos requires an ultra-high bandwidth slice. The applications are endless. In [ 5 ] authors have presented a design of radio access network (RAN) slicing model by characterising diverse radio resource management (RRM) strategies for multi-service 5G scenarios. The model has been designed and tested using a slicing-aware resource allocation procedure that utilised Markov modelling approach to capture the responses for different radio links experiencing diverse user experience. Using network slicing in a 5G network responds to the potential popularity of 5G as the next-generation cellular network that can serve a large number of use cases. The 5G network can provide high-speed network connection with high reliability and low latency, which makes 5G the preferred network for different use cases. The 5G network can be the serving network of IoT. Thus, the base network for all these use cases will be the 5G network. Network slicing should be conducted to efficiently use the underlying resources of 5G networks. The limitation of network slicing in a 5G network is its infancy; it has not been extensively researched and used, thus giving rise to different issues and challenges. For example, network slicing implementation on radio access network (RAN) in 5G environment is a difficult task and calls for complex network designs. The current network architecture needs to be modified to fit the network slicing model. The goal of this work is to create a network slicing model with few modifications to the already existing network architecture of 5G.

Network slicing can be defined as the process of creating slices in the network according to the needs of different end users. The requirement of end users varies from one to another. Thus, the network service provided to these users should vary according to their need. However, the physical network infrastructure is not yet vast and complex enough to serve user needs. Moreover, implementing a user-based network service in terms of physical infrastructure is a difficult task that requires a considerable amount of money, expertise and labour. However, softwarisation and virtualisation of the network infrastructure make providing user-based network services possible. In the context of the 5G network, this feature is important because 5G is deemed to serve a wide variety of use cases. This necessity calls for the concept of network slicing to be implemented in the 5G network. Network slices are created according to demands and are supplied by the telecommunication network, which is 5G. Network slicing involves slice creation, slice isolation and slice management. The process of network slicing will be implemented on the core network as well as on RAN. The concept of network slicing will provide users with small network slices rather than the whole network services. For network slicing to be possible, the techniques that need to be embedded are SDN, which enables the creation of softwarisation abstracts of the network functions, and NFV, which virtualises the network functions. Finally, the virtual network can be sliced in different ways as required.

3 Literature review

This section presents the recent literature based on network slicing. Prior research was focused on network slicing limited to LTE and 4G networks [ 6 ]; however, the emphasis on establishing 5G networks for all use cases has made the network slicing important for today’s telecommunication industry. Although the research on network slicing in 5G networks has been conducted in the recent literature, but these projects were mostly implemented on the core network of 5G. In [ 7 ], the authors highlighted the need of utilising SDN/NFV-based technology to handle the massive growth in data associated with IoT devices. Authors have presented a design and analysis of mathematical model to compare the cost and energy consumption for SDN/NFV network and a traditional 4G network.

In [ 8 ], the authors provided the conceptual description of network slicing in 5G networks and focused on the coexistence of slices from an architectural point of view. The authors added a few methods to enable flexible RAN considering its impact on the 5G network design. Based on the topological information, a mathematical model was presented for the deployment of end-to-end slicing in a 5G network. The network slice implementation algorithm was proposed for three distinct types of network slices. Through simulation, the performance of the proposed algorithm was assessed for different slices. In [ 9 ], the author elaborated the 5G network slicing concept, provided insights on SDN and NFV and emphasised the combination of the two technologies to achieve network slicing. Other works on network slicing involved network slicing on the core network, network slicing on the access network, resource management using network slicing, isolating network slices and improving resource utilisation and latency using network slicing. The authors in [ 10 ] described the 5G network architecture with respect to elasticity and scalability requirements for network slicing to provide customisation at granularity levels. This research provided a personalised mobile telecom (PERMIT) approach for network slicing. This approach acts as a catalyst for structural changes to the current telecommunication system configuration by making changes to the mobile delivery network and services. User mobility patterns, service usage behaviour patterns and dynamics of underlying infrastructures are considered. Also, this research presented the insights on network slicing along with SDN, NFV, mobile edge computing (MEC) and other technologies that will soon become major points in the service-oriented 5G network architecture.

In [ 11 ], the authors discussed different network slicing techniques and pointed out several open research challenges in network slicing. In [ 12 ], the authors described the role and importance of network slicing in vehicle-to-everything (V2X) services with regard to 5G networks by addressing the design for dedicated V2X slices. In [ 13 ], the authors discussed network slicing architecture that features RAN abstraction. The proposed model is based on the principle of an exclusive core network assigned to separate traffic from the appropriate core network and uses a two-level scheduler to abstract and share resources among the slices. As per the requirements for each slice, the proposed architecture provides flexibility by adapting the resource allocation policies as required.

In [ 14 ], the authors proposed RAN runtime slicing architecture that provides an adaptable execution environment for running customised slice instances with desired isolation levels while sharing the same underlying RAN infrastructure. In [ 15 ], the authors provided a cloud-native approach for 5G network slicing by considering the slice life cycle. Given the requirements of different new services, this approach will help serve and deliver such requirements. For example, the proposed approach can help mobile network operators to devise network architectures and plan their deployment scenarios in accordance with the requirements of their business models, use cases and service groups. In [ 16 ] the authors presented a common framework for bringing together and discussing existing works in 5G network slicing in a holistic and concise manner. This proposed framework groups several proposals of slicing according to the architectural layer they targeted. The authors also evaluated the maturity of current proposals and identified several gaps in the literature.

The core concept of network slicing is discussed in [ 17 ]. The environment of the 5G network is shown in this research, and a model for a network slice architecture is provided. The matching process of the network slicing selection matching model is also proposed. In [ 18 ], authors have provided various approaches for RAN slicing. The authors compared the approaches by identifying their advantages and disadvantages based on various scenarios. Finally, analysis and simulation on network slices and isolation are presented. In [ 14 ], the authors described the importance and role of network slicing in a runtime environment in 5G networks and addressed the design for runtime network slicing.

A good understanding of resource allocation framework, which can pave the road for wireless network virtualisation is presented by the authors in [ 19 ]. The authors introduced 5G networks and the importance of slicing and discussed several open issues in 5G network virtualisation. The authors provided a logical architecture for 5G systems based on network slicing. The authors used SDN and NFV technologies to demonstrate the evolution of network architecture along with the implementation of network slicing. Additionally, the authors have also presented handover procedures for mobility management, which offers flexible and agile customised services in network slicing-based 5G systems.

The authors in [ 20 ] proposed a RAN slicing technique based on separation of control and user planes. The authors implemented the proposed architecture to transmit control data at a low frequency and user data at a high frequency. Thus, the created slices are further 3 divided into control and user plane slices. This plane separations and RAN slicing provide system flexibility to satisfy user demands appropriately. In [ 21 ], the authors reviewed the notion of plastic architecture and presented end-to-end network slicing in 5G networks. Several key issues involved in slice selection were identified, and the DTNC mechanism for end-to-end network slice selection was presented in this research. In [ 22 ], the authors have provided a framework for RAN slicing in 5G networks. This framework establishes the information and configuration of RAN node, thus enabling multiple RAN slices with different radio protocol behaviours and different levels of resource allocation and isolation multiplexed over the same cell. This work helps in providing an understanding of different RAN slice features, policies and resources for L1, L2, L3 protocol layers of radio interface. Another comprehensive review that provided a deep insights on SDN and NFV and emphasised on combining these two technologies for establishing network slicing design has been captured in [ 23 ]. Figures  1 and 2 depict a network slicing model presented in [ 23 ] and elaborates on combining these two technologies for effective network slicing.

State-of-the-art network slicing model

SDN and NFV integration framework

In [ 24 ], the authors conducted a comprehensive survey about recent advancements of network slicing with a focus to enable Internet of things applications. The authors have structured the review around selected parameters such as resource levels, function chaining schemes, physical infrastructure as well as security. The authors also discussed the open research areas in network slicing domain.

The purpose of our research is to create a network slicing architecture that will integrate the SDN and NFV technologies to create slices of the 5G network. This article is similar to some of the prior research streams in considering the different components of the network for network slicing, such as the core network and RAN. The author presented an architecture that integrates SDN and NFV with the intention of creating and managing network slices, isolating slices and managing resources. The author also considered several use cases in relation to 5G network slicing and explained different challenges that arise from implementing network slicing. Figure  1 shows the network slicing architecture proposed by the authors based on involving SDN. Figure  2 shows integration of SDN controllers into the NFV architectural framework at the two levels required to achieve slicing. Various ideas have been proposed for network slicing in mobile networks and specifically for the 5G network domain. However, network slicing concept is new to the mobile communication network domain, related works are in their infancy and a detailed overview of the full network slicing architecture in a 5G network is missing. A complete overview of the network slicing model was designed using the previous works and latest technologies, such as SDN and NFV.

4 System components

The 5G-NSUE model has been developed after undertaking a comprehensive review of past and present network slicing systems. The proposed system has been built by utilising software and virtualisation techniques on the underlying network infrastructure to create network slices according to different use cases. With the help of domain experts in SDN, 5G networks, virtualisation and network slicing, the classification was refined according to the most relevant factors for the design, modelling, validation and evaluation of the network slicing system. On the basis of the review and prior knowledge of the field in order to create slices in the 5G network, four main points need to be considered:

selection of network area on which network slicing should be implemented on;

the scope of the slices of the 5G network;

how the network slices should be delivered to different use cases, and

which technologies should be integrated with the network slicing model.

These factors are crucial elements of network slicing architecture and will help provide an understanding of the requirements that should be considered for creating any network slicing architecture on 5G networks. Moreover, these factors are classified with their attributes to provide an in-depth understanding. Previous works studied several of these factors in their architectural model, but did not consider all these factors at the same time. Moreover, previous state-of-the-art models considered using either only SDN or NFV in their architecture. By contrast, the proposed model considered these factors, which are equally important for network slicing. Given that the previous models considered typical cases, such as core network slicing or RAN slicing, the proposed model considered slicing on the core network, RAN and user equipment, which constitute the complete network slicing of the 5G network.

The first considered point is the area for the slicing model in the 5G network. This network area can be divided into three main components that are RAN, core network and the user equipment. These components are the important aspects of the network node that should be considered when deciding which area of the 5G network where network slicing will be implemented on. The main 5G network components include underlying physical infrastructures, such as base stations, end devices, switching centres and mobility management units. These components are important because of the possibility of creating slices of the 5G network in these individual components and in the combination of them. The second considered factor for slicing for slicing model is the network slice scope or the network slicing step, in which the overall slicing processes are performed. The subclasses in this factor are slice creation, isolation and management. As evident by the name, aforementioned components are useful for creating and managing the network slices in a 5G network. This step can be termed as the key part of the system model given that this factor involves the main task of the research. Moreover, the SDN controller is further divided into infrastructure and tenant SDN controllers.

The third factor is 5G network node and considered use cases of the network. The network nodes are subclassed into three groups: RAN, core network and user equipment. The bases for the 5G network are the different use cases that the network will serve. To serve different use cases, the 5G network will use network slicing to create slices with different attributes that are required by the multiple use cases. The importance of this factor is to understand the requirements and be able to create the network slices to feed their necessity and demands. The subclasses in this factor are mobility, resource management, security, low latency and high and low bandwidths. These subclasses show the nature of requirements that need to be facilitated by the network slices. The fourth and final factor in this system model is the use of virtualisation and software techniques. These integrated techniques form the foundation for network slicing in the 5G network architecture and are integral factors that cannot be missed from the system model. The subfactors are SDN and NFV. SDN is simply an abstraction for describing components and functions, as well as the protocols for managing the forwarding plane. This system model concept using NFV emphasises the use of virtualisation for various network node functions.

Table 1 shows the components and sub-components of the proposed network slicing model. The columns of the table present the main attributes of each component and their sub-components along with several common instances for each case. The components column includes the name of the components required in the model while the main attributes column includes value/feature/function for the respective components. Instances are the generic examples for the respective components. Following the table is the component diagram, Fig.  3 illustrates the relationship between these components and their sub-components and how they are linked with each other. This figure shows different components of the 5G-NSUE system model. The four units indicate four different components and their sub-components in the system. The component and sub-component are connected using dotted lines. The solid lines are used to communicate between multiple components or to and from sub-components of the same factor/component. Integrated techniques comprised sub-components used to softwarise and virtualise the physical infrastructure of the 5G network. This step is achieved by using SDN and NFV, which are applied on physical infrastructures such as RAN, core network and user equipment. User equipment is connected to the network via RAN, which is connected with the core network. The core network helps connect with third-party networks, such as the public Internet. By using the virtualised and softwarised components of the network, the network slicing component will cut the slices of the network. The slices are created according to the demands and requirements from the different use cases that are connected with the network. These requirements are received when the request for slices is made by the use case. After the slice is created, the isolation of these slices must be considered depending on the type of slices. This step is performed by the slice isolation sub-component, while slice management component is responsible for the overall management of the slice orchestration and management of network slices. The remainder of this section will define each of the four factors and their subclasses and justify why each factor is used for classification. Diagrams of the classes and subclasses, which make up each of the factors, are illustrated accordingly. Table 1 shows a component table for the network slicing model and shows the required components along with its sub-components. Each component and sub-component are further provided with their attributes and instances in other columns of the table.

Proposed network slicing model. Dotted lines show sub-components whereas solid lines depict an action or process coloured solid line are used to show which process is involved with each component/sub-component. The process belongs to the sub-component from which the solid line starts from. For example, blue solid line belongs to the SDN sub-component as the blue solid line starts from SDN sub-component and ends at RAN sub-component. Blocks are used to group each component and its sub-component to a single unit

4.1 Network node

Network slicing can be created on different areas of 5G network. An important factor is to consider the network area where network slicing is to be implemented. Before the advent of 5G technology, the core network and RAN did not distinguish between the devices that connected with them. The same core network and RAN served all the devices, hence the need for clear distinction between these areas of the network. Network slicing can be implemented on different areas of the network, such as the core network, RAN and user equipment. The different reviewed studies implemented network slicing on these different areas of the 5G network. Several articles have been found that have implemented network slicing on the core network and the RAN, but few instigated network slicing on the end user equipment. Most studies applied network slicing on individual areas only and not combined, such as the core network or RAN only. Carefully selecting the area of the network on which the slicing is to be implemented is important. The most effective configuration for network slicing is the combination of all the three areas, where network slicing is performed at different network nodes and areas.

Figure  4 shows a design architecture of 5G network with different nodes. The main network nodes of the 5G network are RAN, core network and user equipment. The RAN connects the user equipment with the core network. The RAN comprises connected base stations with controllers. For 5G, the RAN (also called NG-RAN) base station (also called gNB) has three main function units: The Centralized Unit (CU), the Distributed Unit (DU), and the Radio Unit (RU), which can be implemented in various combinations. The core network is also incorporated different units, with each unit responsible for performing different functions.

Network nodes of the 5G network architecture

The control and user planes are separated to distinguish between the user plane function and control plane function. Different control plane functions include authentication, policy control, access and mobility and session management. The core network can be connected to third-party networks, such as cloud servers, via the Internet. The purpose of using a network node as part of the model will identify the part of the 5G network where network slicing will be executed/implemented. In addition, this step will determine the extent of the network slicing. For example, network slicing can be performed on only one area of the network or on a combination of multiple areas of the network. As the nodes of the network in which network slicing is increased or combined, the complexity of network slicing will increase. However, doing such might create network slices in multiple nodes and thus complete network slicing on the 5G network, which will increase the performance of the slicing. The subfactors involved in this classification are user equipment, RAN and core network. When we think of network slicing, we mainly focus on core network slicing. To extend this definition, we can also think of network slicing in RAN node. However, performing network slicing on the RAN seems more complex and difficult than performing network slicing on the core network only. Moreover, network slicing can be implemented on end devices or the user equipment. However, the problem with network slicing in user equipment is in its initial phase and network slicing in user equipment seems to be a far-fetched concept at this moment. Nonetheless, the location is still a potential area, and achieving network slicing on user equipment will enhance the overall performance of the 5G network.

4.2 Network slicing

Network slicing can be defined as the technology that enables the creation of different virtual networks on top of physical infrastructures. Network slicing is the central figure in the system model. This component will help create network slices according to various demands, which come from another component of the system model, namely the use cases. Different use cases exist. Thus, the requirements from these use cases are different in nature. These varying demands needs to be fulfilled by today’s 5G network, which is provided with the proposed network slicing component. The Integrated technique component will create a virtualised network scenario in which the physical infrastructure of the 5G network is secondary, and the logical components that are the abstractions of the underlying physical infrastructure are of prime importance and are primary components. These primary or logical components can fulfil specific purposes according to the need from the use cases. The important aspect to consider in this situation is that the logical network is adaptable and can make adjustments according to the changes in needs by devoting more/less resources in the process. With network slicing, the 5G network can now be deployed more quickly given that only fewer functions need be deployed according to the use case (unlike when all functions are being deployed) and the users utilise only what is needed. This network slicing component is dependent on the network nodes, which include the core network, RAN and the end device. The reason for this dependence is that network slicing needs to be implemented on these infrastructures. Network slicing can be deployed on the core network only, on the RAN only or on the combination of both. The sub-components of network slicing involve slice creation, which enables the development of 5G network slices; slice isolation, which isolates the different type of slices from one other; and slice management, which, as the name suggests, manages the overall process from slice creation to slice delivery to the use case.

Figure  5 shows three different layers: the resource, network slicing and service layers. The resource layer consists of the physical resources or the network functions, which are used to provide services to the end users. Before services are delivered to the end users, the resources are first sliced to create different instances called subnetwork instances, which are then utilised to form the network slice instances. Several subnetwork instances may coalesce to form a single network slice instance as depicted by the colour of the blocks. Alternatively, a network slice instance may be directly delivered from the network functions and shown with Network Slice Instance 1, which is created directly from the network function rather than by using subnetwork instances. Finally, the network slice instance is used to create the service instance, which provides specific services to the end users. These service instances are created per the demands of different use cases. The purpose of using network slicing as part of the model is to identify the aspects of network slicing used. For example, most of the reviewed literature uses the slice creation aspect of network slicing, but not all of them considered the slice isolation aspect of network slicing. Accordingly, we used network slicing as part of the model. Moreover, network slicing is the core of this paper’s research topic. Thus, classifying prior studies according to network slicing seems obvious. Different aspects were used as part of the model under network slicing, including slice creation, slice isolation and slice management. Slice creation is mostly used in all the extant research, while few selected literature focused on slice isolation and slice management. Considering the aspect of slice isolation and slice management is crucial because these aspects will identify the efficiency and effectiveness of network slicing; thus, they are used in the model. Creating isolation between the different types of slices is also vital so that they can be delivered to different use cases as required. Furthermore, slice management will ensure that the overall process of network slicing is performed in a controlled way and the slices are processed through slice management and the orchestration unit. The problem with slice management and slice isolation is that they require advanced computation and processing which will increase the model complexity; however, the inclusion of these aspects will possibly ensure the complete package of network slicing.

Network slicing model in a layered approach

4.3 Use cases

Many use cases must be served by the 5G network. The 5G network needs to be sliced according to the varying requirements of different use cases. The emergence of IoT has added to the brackets of use cases that the 5G network must serve. Network slicing must be implemented such that these use cases are delivered with the right network slice according to their demands and requirements. Furthermore, the dynamic nature of use cases adds to the complexity of network slicing. Network slicing must be flexible and dynamic enough to sustain the needs of the changing nature of the requirements of use cases. Use cases have different attributes, such as ultra-high bandwidth use cases, very low-latency use cases, ultra-reliable low-latency use cases, high-bandwidth use cases and massive IoT use cases. Massive IoT [ 25 ] is one of the most anticipated use cases of the 5G network and will require the sliced form of the 5G network. It uses the sliced 5G network to seamlessly connect different embedded sensors all over the world. The attributes of such use case include smart cities, assets tracking and smart utilities up to agriculture industries. Ultra-reliable low-latency use cases use highly available low-latency links for purposes such as remote control of critical infrastructures, smart grid control, the automation of industries, robotics and drones. Enhanced event experience use cases have attributes that are related to VR videos, as well as high-definition and high-fidelity media experiences.

Figure  6 shows a simple demonstration of different use cases to be served by the 5G network slices. Different colours show different types of slices, and slices with similar requirements are grouped together. Different use cases require different types of network slices and thus, the created slices serve multiple use cases, as shown in Fig.  6 . The purpose of utilising use cases as part of the classification is that the use cases will help differentiate the type of slices that will be created. Numerous use cases must be served by the 5G network, and all these use cases require different types of network services and demand different natures of network slices. Thus, with the use of the slicing algorithm, different types of slices can be created and delivered to these use cases. Use cases will help identify the nature of slices that must be created by the 5G network. Thus, considering use cases as part of classification was vital. Different subfactors under use cases were used for classification. The major ones include mobility, resource management, security, IoT, low-latency and ultra-high bandwidth use cases. These different use cases can accommodate many industries, companies and end users that the 5G network will be serving; hence, the classification includes these use case subclasses. The major problem with some use cases, such as mobility, is that it must serve all the mobility aspects of the end user. In reality, mobility requires dynamicity and flexibility in the network slice that is serving the end user with the mobility requirement. Fortunately, network slicing facilitates the creation of a network with high flexibility.

Network slicing use cases

5 Component classification

Based upon the components defined in the previous section, the following section further breaks down the components to the sub-component level and provides a detailed discussion as well as classification of these components with respect to some reviewed articles in this domain.

5.1 Core network

One of the frontline factors in cellular wireless technology is the core network, which remains a highly rich and essential area of innovation as it is the key element of the future of wireless networks. The primary function of the core network is to connect the RAN with the third-party network for providing end-to-end connection. The third-party network instances include public telephone network, switched network and the Internet. The three different planes used in core network functionality are service management, session management and mobility management. In the case of the 4G network, the main function of the core network is to provide an efficient data pipe. The core network can connect to the public Internet quickly by using two of its major functions, which are the serving and the packet data gateways. The mobility management unit in the core network manages the sessions of the user data as the user moves around the network. In the case of the 5G network, the whole core network architecture is designed to provide the network as a service, which makes it a service-oriented architecture. The overall core network is broken down into detailed created functions and subfunctions. These functions include the session management, mobility management, access management and user plane functions. The 5G network core is now designed to function as a flexible network or as a service solution. Creating flexible and dynamic services will enable network slicing to satisfy the demands of the multiple use cases that exists in today’s 5G network domain.

5.2 Radio access network

Radio access network (RAN) is the major sub-component of the 5G network and has been used in the telecommunication industry since cellular technology emerged. It has been evolving ever since through different generations of mobile communication. RAN was used in initial generations such as 1G and 2G, has evolved through 3G and 4G and finally reached the 5G network. The main components within RAN are the base stations and the antennas. These components are responsible for providing network coverage all over the world. Radio sites are the main factor within RAN that are responsible for providing radio access, as well as coordination and management of different resources across multiple radio sites. Networks transmit all over the world by using RAN. Specifically, the RAN transmits the signal to various wireless endpoints, and this signal travels with another network traffic. The major types of RAN include the generic radio access network (GRAN), GSM edge radio access network (GERAN), UMTS terrestrial radio access network (UTRAN) and the evolved universal terrestrial radio access network (E-UTRAN). GRAN is the type of access network that uses base transmission stations and controllers for managing different radio links for the purpose of circuit-switched and packet-switched core networks. GERAN involves the type of access network that mainly provides support for real-time packet data. UTRAN provides circuit-switched and packet-switched services, and E-UTRAN is used for high-data-rate and low-latency communication and focuses only on packet-switched services. Another factor in RAN that must be considered is the RAN controller, which is responsible for controlling the connected nodes. The RAN controller provides functionalities, such as management of radio resources, mobility management and data encryption. Clearly, today’s RAN architectures are mostly based on the separation of control and the user plane. In such scenarios, the RAN controller exchanges the user messages through SDN switches. The separation of the control and user planes aligns with the SDN and NFV techniques that will be integrated with the 5G network architecture for the purpose of network slicing.

5.3 User management

User equipment is another major factor to be considered in network slicing architecture. User equipment involve the end devices employed by the end users that are served by the 5G network slices. These end devices range from mobile devices and personal desktops to high-capacity servers and data centres. The instances of mobile devices include Android, Windows and iOS devices, which refer to the major operating system devices currently used all over the world.

5.4 Slice creation, isolation and management

Slice creation involves creating the virtual network according to demands. Creating slices entails using techniques such as virtualisation and softwarisation. The underlying physical network is virtualised by using SDN and NFV to create network slices. Different types of network slices can be created in the 5G network architecture. The type of network slices created depends on the use cases that require the slice. For example, for low-latency use cases, the created slice would be the ultra-low-latency slice. Besides this, slice isolation is another important factor to consider in network slicing architecture. The objective of slice isolation is to create slices and then differentiate them from among each other depending on the nature and type of use cases they will serve. The different slices of the network must not be mixed up with one another; slice isolation will play a vital part in preventing such occurrence.

Slice management is another aspect of network slicing that will help manage the 5G network slice. This feature will manage the overall process starting from slice creation until the slice is delivered to the appropriate end users. The role of slice management and orchestration unit will be to manage the slice. This unit is integrated into the network slicing architecture and will manage the slice from tasks such as slice scheduling, slice resource management and slice nature.

5.5 Software-defined networking

SDN is one of the major components implemented in the 5G networking architecture in order to reduce limitations often placed by the use of hardware. The major purpose for utilising SDN is to separate the control plane outside the switches and provide external data control using a logical software component called the SDN controller. SDN is simply an abstraction for describing components, their functions and the protocols for managing the forwarding plane. SDN is further subclassified into the SDN controller and SDN manager. SDN also provides management for mobile IP from a remote controller through a secure channel. Moreover, SDN helps solve the inability of mutual access between multiple parts of today’s heterogeneous networks. Currently, the number of mobile network users is rapidly growing. Thus, an expensive upgrade is needed on the hardware elements of backhaul infrastructure. The use of SDN makes performing upgrades easier by deploying new services and applications. The main objective of implementing SDN is to create a network with a completely automated administration, allowing the administrator to manage the network in an efficient manner via a control plane by applying required policies on network routers and switches. In such a setup, the network administrator has complete capability to monitor the whole network remotely. The major concept in SDN is the application of a programmable network infrastructure and the decoupling of the data plane and control plane. Thus, SDN helps provide simplified management of network and facilitates the introduction of new services or any changes in the network. Some of the benefits of SDN application include programmability of the network, centralised management of the network, reduced operational and capital expenses, and agility, flexibility and innovation in the overall network. Although SDN seems to be the solution for the next-generation 5G network to serve multiple use cases, it does have some limitations. A main limitation comes from the computing capabilities and resources of mobile devices; the overhead increases to significant levels with the increase in the mobile user’s request.

5.6 Network function virtualisation

The virtualisation component used in the network slicing architecture is the NFV technology. This architecture concept using NFV emphasises virtualising the entire class of network node functions. These virtualised node functions are then connected to create communication services per the use case demands. A virtualised network function comprises one or more virtual machines that have different software and processes running on them on top of servers, switches, storage devices and cloud infrastructure. Figure  6 illustrates the mapping between the NFV and network slices. Different communication services require network slices to provide the services. These network slices may have subnet/s. This situation means that a network slice can be composed of one or more slice subnets. Each individual subnet is responsible for carrying out a particular network function. These network functions depend on the services required by the use cases. Moreover, the virtual network functions are directly derived from the physical network functions that are provided by the underlying physical infrastructures.

6 Analysis of article classification

Based around the key components defined above, some selected recent articles in this domain were analysed and the results are tabulated in Table 2 . Most of the search results included various network slicing architectures used both in the past and presently, as well as the benefits of using network slicing as an efficient resource utilisation and bandwidth optimisation tool. Few results are focused on isolation and scheduling of network slices. It is to note that only those articles that were published between 2012 and 2020 were selected in this review. In order to capture the use of these classification attributes at application level, Table 3 highlights other features and parameters such as slicing time, resource management, scheduling, bandwidth and scheduling and the implementation of SDN and/or NFV that are considered for the analysis of the selected publications. Furthermore, Tables 4 and 5 present the analysis of different publications based on implementation goal, technique utilised as well as the key feature of this implementation. Additionally this data also highlight the limitation of each of these implementations.

7 Discussion

The following section explores the components of the 5G-NSUE taxonomy by drawing on examples from the literature to demonstrate that the 5G-NSUE components are present in network slicing systems in the 5G network domain and are therefore relevant to such a taxonomy. Furthermore, this section highlights the importance of carefully considering particular solutions for the components. Network slicing was well defined in the 16 chosen publications, but only few described or included network slicing on the core network and RAN in a combined way. Moreover, only two publications considered network slicing on user equipment, which we believe is a necessary factor missing in the 14 other papers. Furthermore, only five papers considered network slicing with respect to the use cases. The publications failed to identify use cases for network slicing because network slicing is in its infancy, and the authors may have deemed use cases as unimportant in this scenario. However, in our opinion, using the 5G network as part of the main network is vital because it will serve all the use cases, and the importance of the use cases in network architecture also needs to be considered. The enabler techniques included in the network slicing model include SDN and NFV. Almost 50% of the chosen publications identified the necessity of such techniques, but they failed to provide insights on how they can be implemented on such systems. The use of SDN and its sub-components such as the SDN controller and SDN manager are missing in the publications. Network slicing on user equipment, which needs to be considered, is also missing. Moreover, use cases that consist of the important factors in network slicing architectures are surprisingly absent. These use cases provide the type of slices that must be created, and thus, the failure to discuss use cases in many publications is surprising. In [ 14 ], the authors discussed the utilisation of use cases for the network slicing model. They examined the design challenges and evaluated the importance of including different use cases in their system model. In [ 15 ], the proposed model which uses the cloud approach considered the importance of different use cases. The authors described the life cycle of the network slice and the requirements from the end users in the slice they offered. They further provided insights on adaptation to the changes on the requirements from end users. Thus, their work considered the importance of use cases in a network slicing model. The authors in [ 18 ] have also studied the utilisation of use cases and the different types of slices, such as mobile broadband slices.

In our opinion, the inclusion of use cases in the network slicing model is important. Some publications involved different use cases in their model, which we believe is because they are valuable for network slicing. Different use cases provide the type of slices that must be created. Moreover, depending on the use cases, the nature of the slice required can change accordingly. Thus, considering such use cases is crucial to create the network slices according to demands. The purpose of creating network slices is to serve end users. Thus, failure to take end users into consideration in the architectural model will create an inefficient and ineffective slicing model. Therefore, consideration of use cases is an integral part of the network slicing model.

It is clear from the reviewed papers that the slicing approaches will be an important part of the future 5G wireless networks. The huge number of Internet of things (IoT) devices and smart devices that rely on cloud application will end up with different types of traffics and Quality of Service (QoS) requirements. The current traditional solutions will not be able to handle such various types of traffic that change rapidly over time. Our proposed model that integrates the SDN and NFV with the 5G slicing architecture will allow better implementation of slicing. The NFV will provide a virtualisation view of underlying resources and the SDN fine-grained control of the traffic for the 5G network. We took into consideration in the proposed models that the IoT nodes are usually based on limited resources in terms of computation and power. The design of the slicing model will be more adaptive to the end services or IoT nodes QoS requirements. This will lead to better use of the resources and better experience from the end-users and applications.

8 Conclusion

Network slicing will be one of the most influential technologies used in the 5G network domain and will change the face of the telecommunication industry. The 5G era requires accommodating rapidly increasing devices and end users in its network with wide diversity. Thus, network slicing is the sought-out option. To enable network slicing, softwarisation and virtualisation of the underlying network infrastructure are needed, which, in turn, are fulfilled using SDN and NFV techniques. This article presented a comprehensive comparison of different studies in the field of network slicing and provided a network slicing architecture by integrating SDN and NFV to create a flexible and dynamic architecture that serves the wide variety of applications in today’s world. A system model for network slicing in the 5G network is also provided. This system model will help support the diverse needs of different vertical industries by making the network architecture flexible and dynamic.

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Authors gratefully acknowledge the continued support received from School of Computing and Mathematics at Charles Sturt University, Australia, for conducting this research.

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PS carried out the investigative study by conducting a thorough analysis of the existing research as a part of his final year Masters research-project. AA and PC supervised PS for this research project and with the conception of project design. SR and MI were involved in manuscript writing and revision process. SA gave some valuable suggestions and participated in the paper revision and editing. All authors have contributed to this research. The final manuscript has been read and approved by all authors. All authors read and approved the final manuscript.

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Subedi, P., Alsadoon, A., Prasad, P.W.C. et al. Network slicing: a next generation 5G perspective. J Wireless Com Network 2021 , 102 (2021). https://doi.org/10.1186/s13638-021-01983-7

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The advanced communication networks require heterogeneous emerging technologies to be combined while enabling various future applications. The integration of 5G wireless and optical technology is considered an unavoidable approach to reach this goal. Based on 5G mobile communications and densification of cells, the upcoming idea of smart city becomes feasible and put on a lot of attention from the research community due to its effect on everyday life’s improvement and modernization. The concept of a smart city should support everything from electrical grids to traffic management and requires the transmission of a huge amount of data. Smart city planning with a reliable communication infrastructure that can provide stringent network requirements is unfeasible without the joint of optical and wireless technologies. This paper aims to provide an overview of recent developments of advanced optical networking to provide 5G transport networks and their applications in connecting a huge number of devices in future smart city infrastructures. The implementation of optical technologies in 5G core networking open numerous questions of how wireless and optical can coexist to provide sophisticated future applications, such as the smart city concept. Within this research, we will provide the answers to some of the key related questions.

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Miladić-Tešić, S., Marković, G., Peraković, D. et al. A review of optical networking technologies supporting 5G communication infrastructure. Wireless Netw 28 , 459–467 (2022). https://doi.org/10.1007/s11276-021-02582-6

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Accepted : 24 February 2021

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Issue Date : January 2022

DOI : https://doi.org/10.1007/s11276-021-02582-6

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5G Wireless Communication and Health Effects—A Pragmatic Review Based on Available Studies Regarding 6 to 100 GHz

Associated data.

The introduction of the fifth generation (5G) of wireless communication will increase the number of high-frequency-powered base stations and other devices. The question is if such higher frequencies (in this review, 6–100 GHz, millimeter waves, MMW) can have a health impact. This review analyzed 94 relevant publications performing in vivo or in vitro investigations. Each study was characterized for: study type (in vivo, in vitro), biological material (species, cell type, etc.), biological endpoint, exposure (frequency, exposure duration, power density), results, and certain quality criteria. Eighty percent of the in vivo studies showed responses to exposure, while 58% of the in vitro studies demonstrated effects. The responses affected all biological endpoints studied. There was no consistent relationship between power density, exposure duration, or frequency, and exposure effects. The available studies do not provide adequate and sufficient information for a meaningful safety assessment, or for the question about non-thermal effects. There is a need for research regarding local heat developments on small surfaces, e.g., skin or the eye, and on any environmental impact. Our quality analysis shows that for future studies to be useful for safety assessment, design and implementation need to be significantly improved.

1. Introduction

Recent decades have experienced an unparalleled development of technologies that are categorized as information and communication technologies (ICT), which include wireless communication used for mobile telephony (MP) and e.g., Wi-Fi by using electromagnetic fields (EMF). The first generation of handheld mobile phones were available for individual, private, customers in a few countries in the late 1980’s. Subsequently, the second (2G), third (3G), and fourth (4G, LTE) generations increased their penetration rates in the society in a dramatic way, so that today there are more devices than inhabitants of the Earth. In addition, Wi-Fi and other forms of wireless data transfer have become ubiquitous, and are globally available. At present we are starting to introduce the next generation, 5G, of mobile networks. Importantly, 5G is not a new technology, but an evolution of already existing G1 to G4 technologies.

With the upcoming deployment of 5G mobile networks, significantly faster mobile broadband speeds and increasingly extensive mobile data usage will be ensured. This is made possible by the use of additional higher frequency bands. 5G is intended to be the intersection of communications, from virtual reality to autonomous vehicles to the industrial Internet and smart cities. In addition, 5G is considered the base technology for the Internet of Things (IoT), where machines communicate with machines (M2M communication). At the same time, a change in the exposure to electromagnetic fields (EMF) of humans and the environment is expected (see, for example [ 1 , 2 ]).

The 5G networks will work with within several different frequency bands ( Table 1 ), of which the lower frequencies are being proposed for the first phase of the 5G networks. Several of these frequencies (principally below 1 GHz; Ultra-high frequencies, UHF) have actually been or are presently used for earlier mobile communication generations. Furthermore, much higher radio frequencies (RF) are also planned to be used at later stages of technology evolutions. The new bands are well above the UHF ranges, having wavelengths in the centimeter (3–30 GHz) or the millimeter ranges (30–300 GHz; millimeter waves, MMW). These latter bands have traditionally been used for radars and microwave links.

Subdivision of the 5G frequency spectrum.

The introduction of wireless communication devices that operate in the high frequency parts of the electromagnetic spectrum has attracted considerable amounts of studies that focus on health concerns. These studies encompass studies on humans (epidemiology as well as experimental studies), on animals, and on in vitro systems. Summaries and conclusions from such studies are regularly published by both national and international committees containing relevant experts (see e.g., [ 3 , 4 , 5 ]. The conclusions from these agencies and committees are that low level RF exposure does not cause symptoms (“Idiopathic Environmental Intolerance attributed to Electromagnetic Fields”, IEI-EMF), but that a “nocebo” effect (expectation of a negative outcome) can be at hand. Some studies suggest that RF exposure can cause cancer, and thus the International Agency for Research on Cancer classified RF EMF as a “possibly carcinogenic to humans” (Group 2B) [ 3 ]. In a recent recommendation of a periodically working Advisory Group for IARC “to ensure that the Monographs evaluations reflect the current state of scientific evidence relevant to carcinogenicity” the group recommended radiofrequency exposure (among others) for re-evaluation “with high priority” [ 6 ]. There is further no scientific support for that effects on other health parameters occur at exposure levels that are below exposure guideline levels, even though some research groups have published non-carcinogen related findings after RF exposure at such levels (see [ 4 , 5 ]). Environmental aspects of this technological development are much less investigated.

Frequencies in the MMW range are used in applications such as radar, and for some medical uses. Occupational exposure to radars have been investigated in some epidemiological studies, and the overall conclusion is that this exposure does not constitute a health hazard for the exposed personnel [ 7 ]. This is due to that exposures for all practical purposes are below the guideline levels and thus not causing tissue heating. However, further studies are considered necessary concerning the possible cancer risk in exposed workers. Medical use of MMW has been recently reviewed [ 8 , 9 ] suggesting a possibility for certain therapeutic applications, although the action mechanisms are unclear.

The 5G networks and the associated IoT will greatly increase the number of wireless devices compared to the present situation, necessitating a high density of infrastructure. Thus, a much higher mobile data volume per geographic area is to be created. Consequently, it is necessary to build a higher network density because the higher frequencies have shorter ranges. The question that arises, is whether using the higher frequencies can cause health effects?

Exposure limits for both the general public and occupational exposure are available and recommended by the WHO in most countries, based on recommendations from ICNIRP [ 10 ] or IEEE [ 11 ] guidelines. These limits, which have considerable safety factors included, are set so that exposure will not cause thermal damage to the biological material (thermal effects). Thus, for 10 GHz to 300 GHz, 10 W/m 2 is recommended as the basic restriction (no thermal effects), with reference values for 400 MHz to 2 GHz (2–10 W/m 2 ) and >2 GHz (10 W/m 2 ). It should be pointed out that the present ICNIRP guidelines [ 10 ] are currently being revised, and new versions are to be expected in the near future. In addition, ICNIRP proposes two categories of recommendations: (1) the basic restriction values based on proven biological effects from the exposure and (2) the reference levels given for the purpose of comparison with physical value measurements. ICNIRP guidelines present no reference values above 10 GHz, only considering the basic restriction values. This is due to that only surface heating occurs since the penetration depth is so small at these frequencies. Therefore any calculations of the Specific Absorption Rate (SAR) values, that take larger volumes into consideration, are not reasonable to perform.

The SAR is the measure of the absorption of electromagnetic fields in a material and is expressed as power per mass/volume (W/kg), where the penetration depth of the electromagnetic fields depends on the wavelength of the radiation and the type of matter. The penetration depth of MMW is very shallow, hence the exposed surface area and not the volume is considered. The appropriate exposure metric for MMW is therefore the power density, power per area (W/m 2 ).

It is of course too early to forecast the actual exposures to 5G networks. However, the antennas planned for 5G will have narrow antenna beams with direct alignment [ 12 ] to the receiving device. This could possibly significantly reduce environmental exposure compared to the present exposure situation. However, it is also argued that the addition of a very high number of 5G network components will increase the total EMF exposure in the environment, and that higher exposures to the higher frequencies can lead to adverse health effects.

Therefore, the question arises, what do we know so far about the effects on biological structures and on health due to exposure to the higher frequency bands (in this review we consider 6–100 GHz, since lower frequencies have been extensively investigated due to their use in already existing wireless communication networks)? Do so-called “non-thermal” effects (effects that occur below the thermal effect threshold) occur, that can lead to health effects? Is there relevant health-oriented research using the 5G technology relevant frequencies? Is there relevant research that can make a significant contribution to improving the risk assessment of exposure to the general population? Answers to these questions are necessary for a rapid and safe implementation of a technology with great potential.

2. Materials and Methods

This review takes into account scientific studies that used frequencies from 6 GHz to 100 GHz as the source of exposure. The review is based on available data in the field of public literature, papers written in English until the end of 2018 (PubMed database: www.ncbi.nlm.nih.gov/pubmed ), EMF-Portal ( www.emf-portal.org ), and other relevant literature such as documents from ICNIRP, SCENIHR, WHO, IARC, IEEE, etc.). In addition, more refined research was conducted when necessary from sources that were not included in the above-mentioned databases (relevant abstracts from conferences, abstract books, and archives of journals). The resulting studies were examined for technical and scientific data and presented in the supplementary Table S1 .

As a pragmatic approach, we interpreted the results as a “response” when the authors themselves reported the result as an “effect/response” based on a statistical analysis and the p -value < 0.05.

Next we defined necessary criteria for study quality, both from a biomedical and physical point of view (see [ 13 ]). The results of the studies were (if possible) analysed for correlations with study quality according to the correlation approach done by Simkó et al. [ 14 ]. The studies were analysed with reference to a minimum of criteria in terms of experimental design and implementation. The following criteria were considered: were the experiments performed in the presence of an appropriate sham/exposure control, temperature control, positive control, were the samples blinded, and was a comprehensive dosimetry presented.

The study is divided into a descriptive part, which covers the description of all selected studies, their exposure conditions, frequency ranges (6 GHz to 100 GHz), dose levels, etc., as well as the biological results, presented in a Master-Table ( Table S1 ). Review articles were not considered. The outcomes of the studies were furthermore analyzed and discussed according to frequency domains, and power density and exposure duration. If appropriate, we include an evidence-based interpretative part regarding risk from exposures according to the criteria of SCHEER [ 15 ].

In the following, health-related published scientific papers dealing with frequencies from 6 GHz to 100 GHz (using the term MMW for all the frequencies) are described in detail. It should be noted that there are no epidemiological studies dealing with wireless communication for this frequency range, thus, this review will cover studies performed in vivo and in vitro.

Thermal biological effects of radiofrequency electromagnetic fields occur when the SAR values exceed a certain limit, namely 4 W/kg (general population exposure limit: SAR 0.08 W/kg), which causes a tissue heating of 1 °C. However, in the literature, biological effects below 4 W/kg SAR values have been described. Since such effects are considered to be not due to warming, they are termed non-thermal effects. In the present review, in some individual studies, the authors interpreted thermal effects as “no effect”. Those ones and studies without response/effect of MMW exposure were considered as “no response/effect” in our present analysis.

3.1. Grouping of Selected Parameters

For analysis, 94 publications were identified and selected from the accessible databases (in vivo and in vitro) [ 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 ]. It should be noted that the total number of individual examinations is larger than the number of publications, since some authors investigated several physical and/or biological conditions in the same publication.

Various biological endpoints have been identified, which are referred to as “response” or effects when appropriate. Since the list of these endpoints is relatively long, we have not mentioned them in detail, but summarized them in groups: Physiological, neurological, histological changes, or in in vitro studies gene or protein expression, cytotoxic effects, genotoxic changes, and also temperature-related reactions.

For a detailed analysis, a “Master-table” ( Table S1 ) was prepared in which all parameters considered in the studies were included. The table contains the following information: frequency, in vivo or in vitro study (the latter distinguishes between primary cells and cell lines), power density, exposure duration, biological endpoints, and response. Some studies lack information on individual parameters. For example, a publication had to be excluded completely because there was no information about the frequency. In nine studies the power density data were absent and in seven studies the calculated SAR values were provided instead of the power density. In ten studies, the exposure time was not given.

The 45 in vivo studies were mainly conducted on mammals (mouse, rat, rabbit) and a few on humans. In some studies, bacteria, fungi, and other living material were also used for the experiments. 80% of all in vivo studies showed exposure-related reactions.

Primary cells (n = 24) or cell lines (n = 29) were used in the 53 in vitro studies, with approximately 70% of the primary cell studies and 40% of the cell line investigations showing exposure-related responses ( Table 2 ).

Overview of the total number of publications examinations.

All identified studies were analyzed as a function of frequency. For this purpose, frequency domains (groups) have been created ( Figure 1 ) to analyze and illustrate the results. The frequency groups from 30 to 60 GHz were grouped in ten-GHz increments (up to 30, 30.1–40, 40.1–50, 50.1–60 GHz). The frequency range 60–65 GHz was extra analyzed as in this group a larger number of publications was identified (in comparison to the other groups). Due to the low number of publications above 65.0 GHz, data was merged into the groups of “65.1–90” and “above 90 GHz”. As shown in Figure 1 , the majority of studies show a frequency-independent response after MMW exposure.

The number of publications as a function of frequency domains. The black line represents the total number of publications, and bars represent the in vivo (dark blue) and in vitro (light blue) studies with biological responses.

3.1.1. Frequency Ranges

All data regarding the individual papers are found in Table S1 .

Up to 30 GHz

The first group “up to 30 GHz” was introduced since some of the 5G frequencies fall within this frequency range. Unfortunately, there are only two publications in this group, both showing responses to the MMW exposure. A study that was conducted on bacteria and fungi showed an increase in cell growth [ 58 ]. The other in vitro study was performed on fibroblasts (25 GHz, 0.80 mW/cm 2 , 20 min), with genotoxic effects observed at high SAR levels (20 W/kg) [ 24 ]. A graphical presentation of the outcomes is presented in Figure 1 for this and all other frequency domains.

Frequency Group 30.1–40 GHz

As shown in Figure 1 , responses were detected in approximately 95% of the 19 studies. In all in vivo studies responses were described after exposure [ 25 , 27 , 36 , 37 , 55 , 56 , 78 , 79 , 87 , 91 , 103 , 104 ]. Endpoints ranged from recorded footpad edema, which is a frequent endpoint for the measurement of inflammatory responses, to morphological changes, changes in skin temperature, blood pressure, heart rate, body temperature, neuronal electrical activity, and EEG analyses. Protein expression studies, oxidative stress marker measurements, histological investigations, and induction of cell death (apoptosis) were performed. Only one study used lower power densities (0.01 mW/cm 2 , 0.1 mW/cm 2 ; SAR: 0.15, 1.5 W/kg; 20 min, 40 min) to study inflammatory responses [ 27 ]. The authors determined the frequency-dependent anti-inflammatory effect as a function of power density and exposure duration and did not rule out temperature-related effects. The power densities of the other in vivo studies were extremely high (10, 75, 500–5000 mW/cm 2 ), so the induced effects were likely temperature dependent.

Eight in vitro studies were performed [ 18 , 20 , 47 , 91 , 97 , 99 , 101 , 102 ] of which seven reported responses. In one study [ 99 ], human blood cells ( ex vivo ) were exposed to MMW for 5, 15 and 30 min (32.9–39.6 GHz, 10 mW/cm 2 ). The activation of the cells was examined in the presence or absence of bacteria. It was shown that in the presence of bacterial activation and after 15 min of exposure, the cells were activated to release free radicals. These results were similar to the heated samples (positive controls), so a temperature effect is plausible. The induction of differentiation of bone marrow cells in to neuronal phenotype cells was also demonstrated (36.11 GHz, 10 mW/cm 2 , 3 × 10 min every 2 h for 24 h) [ 97 ]. In two studies, temperature-related reactions were described at the protein level [ 18 , 91 ]. When the cell cultures were cooled during exposure to prevent the induced temperature increase, no responses were detected.

In three publications, a research group described cell cycle changes, induction of cell death and activation of differentiation processes in primary cells (rat bone cells and mesenchymal stem cells) after exposure to 30–40 GHz (4 mW/cm 2 , different exposure durations) [ 47 , 101 , 102 ]. Unfortunately, the minimum quality criteria were not fulfilled in any of the three studies, mainly because there were no temperature controls.

Frequency Group 40.1–50 GHz

In the 40.1–50 GHz frequency group, 26 studies were identified, 13 in vivo [ 16 , 17 , 26 , 48 , 49 , 51 , 53 , 65 , 69 , 74 , 80 , 84 , 98 ] and 13 in vitro [ 29 , 30 , 31 , 62 , 64 , 86 , 89 , 92 , 93 , 100 , 105 , 107 ] with nine studies showing responses. A large number of studies have tested cell biology endpoints such as cell proliferation, gene or protein expression, and changes in oxidative stress. In addition, immunological, neurological, morphological and genotoxic effects were investigated. The power densities used vary enormously, from 0.02 to 450 mW/cm 2 , and one publication gave no information.

In healthy volunteers, a double-blind study was performed to investigate the effects of MMW on experimentally induced cold pain (42.25 GHz, <17.2 mW/cm 2 , 30 min) [ 74 ]. The authors found no difference from the placebo effect. This study was a repeat of a previous study with volunteers and the results of the older study could not be confirmed. The other four in vivo studies with no detectable effects were investigating genotoxic effects or oxidative stress [ 17 , 48 , 49 , 98 ].

Five in vivo publications addressed the effects of MMW on the immune system of mice or rats, finding activation of the immune system at both the cellular and molecular levels (41.95 or 42.2 GHz, 19.5 μW/cm 2 , 0, 1, 31.5 mW/cm 2 , 20 min or intermittently over 3 days) [ 26 , 48 , 51 , 53 , 84 ].

MMW exposure of frog isolated nerve cells, (41.34 GHz, 0.02, 0.1, 0.5, 2.6 mW/cm 2 , 10–23 min) lead to a reduction of the action potential frequency. Interestingly, the effects at higher power density (2.6 mW/cm 2 ) were similar to conventional heating [ 49 ].

One study detected an increase in the motility of human spermatozoa after 15 min of exposure (42.25 GHz, 0.03 mW/cm 2 ) [ 100 ]. Additional in vitro tests have identified the formation of free radicals, the activation of calcium-dependent potassium ion channels (around 42 GHz, 100, 150, 240 μW/cm 2 , 20–40 min) as well as changes at the cell membrane in exposed cells [ 29 , 30 , 100 ].

No responses on cell biological endpoints (cell cycle changes, cell death, heat shock proteins) were detected in four additional in vitro studies.

Frequency Group 50.1–60 GHz

We identified 16 studies in the frequency group 50.1-60 GHz (six in vivo, ten in vitro) and 60% of the studies showed responses to MMW exposures [ 21 , 23 , 35 , 38 , 43 , 46 , 59 , 61 , 72 , 77 , 81 , 83 , 85 , 94 , 109 ].

In five of the in vivo studies very different responses were shown. In a study on healthy volunteers, the authors wanted to find out whether the human skin at a so-called acupuncture point has different dielectric properties during exposure to MMW. They found that these properties change during exposure to 50–61 GHz from the surrounding skin [ 23 ].

A pilot study on mice (60 GHz, 0.5 mW/cm 2 , lifelong exposure for 30 min/5 days a week) showed that MMW exposure affects cancer-induced cells and increases in motor activity of healthy mice [ 61 ].

In rats, the influence of 54 GHz, 150 mW/cm 2 , on an area of approximately 2 cm 2 on the head was examined [ 81 ]. This transcranial electromagnetic brain stimulation induced pain prevention and prevented the conditioned avoidance response to a pain stimulus in 50% of the animals. However, no changes were detected when serotonin inhibitors were previously administered. Therefore, the authors concluded that transcranial electromagnetic brain stimulation promotes the synthesis of serotonin, a transmitter that changes the animals’ pain threshold.

The effects of MMW were also tested (60 GHz, 475 mW/cm 2 , 1.898 mW/cm 2 , 6, 30 min) on rabbit eyes, describing acute thermal injuries of various types [ 38 ]. The authors also pointed out that the higher temperature just below the eye surface could induce injury.

Neurological investigations were performed on leeches (60 GHz, 1 min, 1, 2, 4 mW/cm 2 ) [ 77 ] and electrophysiological studies were performed on frog oocytes (60 GHz, up to 5 min) [ 85 ]. In both experimental systems effects were described, which were induced by the temperature rise.

Cell biological and morphological changes after exposure to 0.7–1.0 μW/cm 2 (intermittent) were reported in three in vitro studies [ 72 , 83 , 94 ], with two publications providing no information regarding power density or exposure duration. At the level of protein analysis and total genome analysis no changes were identified in four in vitro studies [ 35 , 46 , 59 , 109 ].

Frequency Group 60.1–65 GHz

The number of studies in the 60.1–65 GHz frequency group is 27. Of these, twelve reported effects from exposure to MMW, and no responses were found in 15 studies.

The in vivo studies investigated different topics [ 23 , 27 , 44 , 52 , 67 , 68 , 70 , 71 , 73 , 75 , 76 ]. Thus, two studies examined the effects on tumor development in mice injected with tumor cells [ 52 , 70 ]. In one of the studies it was reported that exposure to 61.22 GHz, 13.3 mW/cm 2 , inhibited the growth of melanoma cells (exposure 15 days after tumor cell injection, 15 min/day) [ 70 ].

Other publications from one research group investigated the potential of MMW for pain relief and the associated biological mechanisms of action [ 67 , 71 , 73 , 75 , 76 ]. Several of the studies were performed on mice skin exposed to 61.22 GHz for 15 min. The most commonly used power density was 15 mW/cm 2 . Another study addressed the dose issue with no effect below 1.5 mW/cm 2 . The authors’ conclusion is that MMW can lower the hypoalgesia threshold, which is likely mediated by the release of opioids.

The effects of 61.22 GHz exposure of mice were examined also with respect to the immune system [ 52 ]. The animals were exposed on three consecutive days for 30 min per day. The exposure caused peak SAR values of 885 W/kg on the nose of the animals where the exposure took place. The power density was 31 mW/cm 2 and the measured temperature rise reached 1 °C. It was found that MMW modulates the effects of the cancer drug cyclophosamide. In particular, the T-cell system of the immune system was activated and various other immune system relevant parameters affected.

The similar exposure condition was used in a study on gastrointestinal function, however no effects were identified [ 68 ].

A single exposure for eight hours (61 GHz, 10 mW/cm 2 ), or five times four hours, did not cause eye damage to rabbits and rhesus monkeys [ 44 ]. It should be emphasized that several of the mentioned studies come from the same laboratory, and all criteria for the study quality are met. However, the authors were able to replicate their own findings on pain relief whereas other laboratories have not replicated this work. In the in vitro studies, various biological endpoints were examined [ 28 , 32 , 33 , 34 , 42 , 45 , 50 , 59 , 60 , 66 , 83 , 88 , 94 , 95 , 108 ].

In one study, neurons of snails ( Lymnea ) were exposed at 60.22–62.22 GHz and no non-thermal responses on the ion currents were identified [ 28 ].

In a series of investigations with nerve cell-relevant cell lines, the dopamine transmission properties, stress, pain and membrane protein expression were investigated (60.4 GHz, 10 mW/cm 2 , 24 h) and no responses were detected [ 32 , 33 , 34 , 59 , 60 , 108 ].

The same exposure setup has also been used in studies examining different stress response related genes (0.14–20 mW/cm 2 ) [ 59 ]. No effects were found at the gene expression level. Interestingly, the overall genome impact was influenced when the exposure (60.4 GHz, 20 mW/cm 2 , 3 h) of the primary human keratinocytes was combined with 2-deoxyglucose, a glucose-6- phosphatase inhibitor. This co-exposure caused a change in the amount of six different transcription factors, the effect differing from the effect of 2-deoxyglucose alone and 60.4 GHz alone (both factors alone induced no changes).

Other studies also examined human keratinocytes and astrocytoma glial cells after exposure to 60 GHz (0.54, 1 and 5.4 mW/cm 2 ) [ 60 , 108 ]. Various parameters such as cell survival, intracellular protein homeostasis, and stress-sensitive gene expression were investigated. Also, in these studies, no effects were observed. In contrast, in one publication, the elevation of an inflammatory marker (IL1-β) was observed in human keratinocytes after exposure (61.2 GHz, 29 mW/cm 2 , 15, 30 min), while other inflammatory markers (chemotaxis, adhesion and proliferation) have remained unchanged [ 95 ].

Another type of study was performed on rat brain cortical slices [ 66 ]. The brain slices were exposed to a field of 60.125 GHz (1 μW/cm 2 ) for 1 min, and then specific electrophysiological parameters were measured. In many slices, transient responses on membrane characteristics and action potential amplitude and duration were observed. The exposure caused a temperature rise of the medium (of 3 °C) in which the sections were stored. Interestingly, a chronically induced Ca 2+ blockade did not affect the MMW response.

Frequency Group 65.1–90 GHz

The studies in the frequency group of 65.1 to 90 GHz were performed both in vivo and in vitro in a total of 14 articles (four in vivo and 11 in vitro investigations). The studies vary widely, based on different hypotheses, biological endpoints, power densities, and exposure durations. In addition, some studies have used biological materials to identify physical properties such as dielectric properties and skin reflection coefficient. The latter studies are discussed in Section 4.2 .

Four in vivo studies reported responses after MMW exposure. One study examined the dose of eye damage (especially damage to the corneal epithelium) [ 40 ]. The dose was calculated as DD 50 (based on the results for which the probability of eye damage was 50%). The experiments were carried out on rats with an exposure of 75 GHz, the DD 50 value being 143 mW/cm 2 .

Other in vivo studies were performed on rats and mice as well as on insects [ 27 , 42 , 57 ]. The study on mice used different frequencies of 37.5 to 70 GHz, with power densities of 0.01 and 0.3 mW/cm 2 for 20 to 40 min. A single whole-body exposure of the animals reduced both the footpad edema and local hyperthermia on average by 20% at the frequencies of 42.2, 51.8, and 65 GHz. Other frequencies had no influence.

The study on insects ( Chironomidae ) focused on DNA effects of giant chromosomes of the salivary glands of the animals with different frequencies (64.1–69.1, 67.2, 68.2 GHz) [ 42 ]. All frequencies, using power densities <6 mW/cm 2 , caused a reduction in the size of a particular area of the chromosome. This in turn led to the expression of certain secretory proteins of the salivary gland.

Different aspects were studied in the in vitro studies [ 18 , 28 , 39 , 50 , 64 , 72 , 83 , 89 , 94 , 106 ], where nerve cell function was investigated in three studies. Two studies used nerve cells from the snail Lymnea that were exposed at 75 GHz for a few minutes at very high SAR levels (up to 4200 W/kg, power density was not reported) [ 28 , 39 ]. The authors observed thermal effects on the ion currents and the firing rate of the action potentials. Another study also described thermal effects on transmembrane currents and ionic conductivity of the cell membrane. Again, the exposure was at very high SAR levels (2000 W/kg), and the authors emphasized the temperature dependence of the reaction.

Broadband frequencies (52–78 GHz) have been used in several publications, mainly investigating the effects on cell growth and cell morphology as well as the ultrastructure of different cell lines [ 50 , 72 , 83 , 94 ]. The values for the power densities were not given consistently but appear to have been very low (not higher than 1 μW/cm 2 ). The results indicated the inhibition of cell growth, accompanied by changes in cell morphology.

Another group of studies used hamster fibroblasts, BHK cells, and exposed the cells at 65 to 75 GHz, with the power density reaching 450 mW/cm 2 [ 18 , 64 , 89 ]. The authors noted the inhibition of protein synthesis and cell proliferation as well as cell death at higher power densities. In a study using human dermal fibroblasts and human glioblastoma cells, no effects at the protein level (proliferation or cytotoxicity markers) were detected (70 GHz and higher, in 1 GHz increments; 3, 70 or 94 h) [ 106 ]. Power densities varied across frequencies, ranging from 1.27 μW/cm 2 in the lower frequency range to 0.38 μW/cm 2 at higher frequencies.

The in vitro studies in this group are similar to the in vivo studies in their diversity. The majority of studies in which responses were reported are thermal-effects due to MMW exposure. In three studies, responses at low power densities were described, but all results were from the same laboratory, and were not replicated by others. Moreover, the quality of these studies is questionable, as the quality criteria were not met.

Frequency Group 90.1–100 GHz

Eight out of eleven studies in the 90.1–100 GHz frequency group are in vitro studies [ 22 , 41 , 57 , 82 , 90 , 96 , 106 ]. The three in vivo investigations addressed a variety of issues including acute effects on muscle contraction, skin-reflection properties (which are more of a dose-related than health-related issue), and skin cancer [ 19 , 54 , 57 ]. The rat skin cancer study (one to two weekly, short-term exposures at 94 GHz, 1 W/kg; DMBA-initiated animals) did not show any positive outcome [ 54 ]. Another study examined the muscle contraction of mice and described some responses [ 19 ]. Again, 94 GHz was used, but power density or SAR values were not reported.

Seven of the eight in vitro studies showed responses after MMW exposure. In some studies, primary neurons were used to study the cytoskeleton (94 GHz, 31 mW/cm 2 ) [ 82 ] or specific electrophysiological parameters (90–160 GHz) [ 22 ]. In the latter study it was found that the observed responses were more likely due to interactions with the cell culture medium than with the cells, although the mechanisms of action were not clear. Other studies identified responses on the DNA integrity (100 GHz and higher) [ 41 ] or described changes in intracellular signaling pathways (94 GHz, 90–160 GHz) using different cell types [ 57 , 96 ]. The exposure time ranged from minutes to 24 h for partially unknown exposure values. In one study no cytotoxic influence at power density levels of a few μW/cm 2 was detected in either normal or in tumor cells.

3.1.2. Power Densities

All identified studies were analyzed as a function of the used power densities. The studies were grouped depending on the power density as follows: below 1; 1.1–10; 10.1 to 50; 50.1–100, and 100.1 mW/cm 2 or higher. Studies that do not provide information on power density or SAR values are not displayed in these groups. As shown in Figure 2 , the vast majority of studies show responses regardless of the power density used.

The number of publications as a function of power density. The black line represent the total number of publications, and bars represent the in vivo (dark blue) and in vitro (light blue) studies with biological responses.

3.1.3. Exposure Duration

Exposure duration of the studies was also grouped for data analysis ( Figure 3 ). The time groups were selected as seconds to 10 min; 10–30 min; 30–60 min; over 60 min-days and alternately/intermittently. The groups were selected so that the used exposure times and the number of studies are meaningfully summarized. Here, too, it becomes clear that the majority of all studies show responses regardless of the exposure time. Interestingly, longer exposure times (over 60 min—days) seemingly lead to fewer reactions than in the other groups.

The number of publications as a function of exposure duration. The black line represent the total number of publications, and bars represent the in vivo (dark blue) and in vitro (light blue) studies with biological responses.

3.2. Studies without Responses

Table 3 shows the number of studies in which no responses were detected after or during MMW exposure. As “no response” also such investigations were referred to, which were considered by the authors themselves as such. This means that in some cases the observed effects were described as temperature-related and not as a non-thermal MMW effect.

Studies without responses.

Few in vivo studies have shown no response at all. Noticeable is the frequency group 40.1–50 GHz, in which 6 studies were identified. These studies investigated immunosuppression, genotoxic effects, changes in pain sensitivity, and changes in enzyme activity. One study was carried out on bacteria and fungi.

There are a variety of in vitro studies in which no responses were detected. Interestingly, studies on protein or gene expression levels often failed to detect any changes after MMW exposure. This could be due to the fact that in in vitro studies the possibility of non-thermal effects were specifically investigated, where cooling was used to counteract the temperature increase.

3.3. Quality Analysis

We analyzed the quality of the selected studies according to specific criteria [ 14 ]. The studies were categorized by the presence of sham/control, dosimetry, positive control, temperature control, and whether the study was blinded. The presence of these five criteria while performing an MMW study is the minimum requirement for qualifying as a study with sufficient technical quality.

Of the 45 in vivo studies, 78% (35) demonstrated biological responses after exposure to MMW. Of all studies, 73% were performed with sham/controls, 76% employed appropriate dosimetry, 44% used positive control, and 67% were done under temperature control conditions ( Figure 4 ). Unfortunately, only 16% of the studies were performed according to protocols that ensured blinding and only three publications were identified that met all five criteria [ 26 , 51 , 53 ]. If the blinding criterion was excluded, 13 studies could be identified that met the remaining four criteria. Considering three criteria only, namely sham, dosimetry, and temperature control, 40% (20 papers) were identified. Thus, the quality of the in vivo studies is unsatisfactory.

The quality of all publications: The number of in vivo (top) and in vitro (bottom) experiments (blue: no reaction, red: reaction) using the listed quality features (y-axis). The spider web shows the percentage of the quality characteristics in all examinations.

Out of the 53 in vitro studies, 31 showed biological responses. Only in 13 studies (42%) were three of the five quality criteria satisfied, namely the presence of sham/control, dosimetry, and temperature control ( Figure 4 ). Positive controls were used in 47% and only one study was performed with blinded protocol (2%).

These results show that the number of examinations and the quality criteria are insufficient for a statistical analysis. It should be stressed that this quality analysis covers all publications dealing with the responses/effects of exposure to 6 to 100 GHz MMW, irrespective of the endpoints tested. To perform a correlation analysis, a larger number of comparable studies (e.g., identical endpoints in a frequency group) would be required.

4. Discussion

The first relevant observation during the analysis of the studies is that in most publications the aim of the investigations has been to determine the effects of MMW exposure for medical purposes. This means that the exposure devices used primarily come from medical applications (therapy or diagnostics). Very few publications dealt with health-related issues after MMW exposure in general, or with the specific topic of 5G. Therefore, the 94 publications are very heterogeneous.

We divided the frequency bands into seven ranges and placed the studies in the relevant groups. All available information on physical and experimental parameters was collected, but the exact number of experiments in each study was not taken into account. (One publication can contain more than one experiment.) Therefore, it is the provided numbers of studies/publications that constitute the data set, not the exact numbers of experiments performed, which is significantly higher.

This report does not provide a statistical analysis of the correlation between the exposure conditions and the results, which was our original ambition. In the correlation study according to Simkó et al. [ 14 ] a frequency group was selected, with only one group of biological endpoints considered. About one hundred, exclusively in vitro, studies were identified and broken down into individual experiments in that paper. In this way, the number of experiments was sufficient to perform a correlation analysis. In the present review, the spread of biological endpoints in the individual frequency groups and the models used (in vivo and in vitro) is large and the number of studies is very low. Therefore, it was not possible to group the studies by specific endpoints and perform a statistical analysis.

Interestingly, more than half of the studies (53 publications) were conducted in the frequency bands 40.1–50 and 60.1–65 GHz (with different models and endpoints). One possible reason for this is that medical use of MMW has a long tradition in Eastern Europe. These applications use specific frequencies that fall in these two frequency groups. The studies were conducted with the aim of testing specific effects with medical relevance. In these two frequency groups, the “with responses” percentage was generally lower than in the other frequency bands (see Figure 1 ), where a majority of studies showed responses to exposure.

With regard to the power densities used, about half of the studies were carried out in the range up to 10 mW/cm 2 ( Figure 2 ). This value is ten times higher than the current ICNIRP exposure guideline [ 10 ] for the general population. Based on available data, there is no indication that higher power densities cause more frequent responses, since the percentage of responses in all groups is already at 70% ( Figure 2 ). One exception from this high response rate is the group 50.1–100 mW/cm 2 , where the proportion of studies with reactions is slightly lower (54%). However, the total number of examinations (11) is relatively small in this group.

The results of some of the studies may suggest that exposure to power densities at or below the guideline recommendations induce biological effects. There are, however, some arguments against it. One of these is the apparent heterogeneity of the study design and the outcomes studied. There are very few (if any) independent replication studies that confirm the reported results. It is also noteworthy that there is no trend towards a classic dose-response pattern where stronger or more frequent effects would be caused by higher exposure levels. Since the studies with conditions promoting tissue warming show no greater effect than below the guideline values (1 mW/cm 2 ), this would either mean that the same interactions are present at all power densities tested, or that experimental artifacts unknown to the scientists are present.

The most important physical experimental parameter is the temperature during exposure, therefore, the temperature must be consistently controlled. The need for stringent temperature control is not an insignificant or trivial matter and has been neglected or at least undervalued in many studies. Although some authors report that they performed specific temperature measurements during the experiments, this does not necessarily mean that this represents the actual temperature in the biological material. Measurements can be made, for example, in the surrounding medium but not in the exposed tissue or in the cell. It also has to be considered that the “bulk” heating (from outside to inside with a certain time course) can differ from a heating that occurs at a rather limited point (“hot spot”). In addition, the intensity of a short burst can be lost if the measurements are based on average exposure times. Such errors and problems are possible factors that have contributed to the questionable interpretation of “non-thermal effects” in some studies.

Effects after MMW exposure were shown at all exposure times with no clear time dependency. The data presented shows one exception, namely in the group “>60 min to days”, where fewer reactions were detected ( Figure 3 ). It has to be taken into account that 27 examinations were carried out in this group, 23 of which were in vitro studies. In vitro experiments can be carried out under cooling, therefore the results can be different (see further below).

Two research groups together provide 30 of the 94 publications in the data set, and could thus possibly have a large impact on the analysis of the outcomes. One group presented at least 21 publications (42.25 and 61.82 GHz; 10 to 30 mW/cm 2 ; with different exposure durations), with a variety of in vivo and in vitro studies, which mostly reported responses to exposure. The other group mainly studied gene and protein expressions (60 GHz; 5.4 to 20 mW/cm 2 ; exposure durations from minutes to days) and found mainly no responses. Studies from both groups adhered well to the quality criteria in our analysis.

4.1. Temperature Controls in In Vitro Studies

In vivo studies that are performed within or directly on the living organism have shown both thermal and purportedly non-thermal effects after or during MMW exposure. In vitro studies are carried out on cells and most experimental parameters can be accurately set and observed. Cell cultures can thus be very carefully controlled, e.g., an induced temperature increase can be counter-cooled. Many in vitro studies considered in this review were performed using cooling of the cell culture vessels and the authors did not detect any non-thermal effects in these studies. In in vivo studies counter-cooling is not possible, thus it is very difficult to differentiate between thermal and non-thermal reactions. Therefore, in vivo and in vitro studies regarding the induced effects cannot be directly compared. An accurate dosimetry could solve this problem.

4.2. Dosimetry

It is important to know what the exposure of the MMW will be due to the expected introduction of a large number of 5G wireless communication devices. Given the novelty of the technology, it is currently unlikely that a large number of relevant exposure assessment studies will be available. However, an example from a recent study [ 110 ] shows that a “typical” office environment with wireless communication transmitters (5.50 GHz) leads to power densities well below the exposure guideline limits. Thus, the maximum power density was measured at 0.89 μW/cm 2 .

Partly (n = 25) the experimental studies on biological and health effects of MMW exposure are at or below the ICNIRP exposure guidelines. The power densities were often chosen so that the exposure caused no or very moderate tissue warming (<1 °C), namely in the range of 1 to 10 mW/cm 2 . Since the penetration into the tissue of these frequencies are on the order of millimeters and below, it is important to study biological effects directly or indirectly related to skin and eyes exposure. As mentioned previously, the number of available studies in the 6–100 GHz frequency range is relatively low, which is in contrast to the number of studies for lower radio frequencies. Similarly, the number of tissue dosimetry studies (especially for the skin) is very limited. However, such studies are very relevant because they show how certain exposure parameters can influence the energy input and thus the thermal behavior of the skin.

Currently, both the ICNIRP guidelines and the IEEE standards are being revised to replace the SAR values with power density above 6 GHz. However, it has already been recognized that there is a reactive near field close to the transmitter (around the antennas). Here, the energy is not radiated, but the energy envelopes the antennas. The question is whether these “reactive near fields” are important for the energy delivery to a human body near the transmitter? If this is not the case, it is sufficient to comply with the existing exposure limits based on free space power density measurements. On the other hand, a strong reactive near field would considerably complicate the exposure situation [ 111 ]. Therefore, for dosimetry modeling of distances (from the antenna) below the wavelength of the MMW (mm), temperature measurements should rather be performed in suitable phantoms rather than direct measurements of the power densities in the free space [ 111 ].

The question is how reliably the power density (in free space) can be extrapolated to possible temperature increases in human tissue? For example, Neufeld et al. [ 112 ] found that 10 GHz “bursts” (considered “safe” by ICNIRP and IEEE) can cause temperature increases of >1 °C if the burst duration is long enough. It was also discussed whether the average values of the power densities for the safety assessment are the right ones. In addition, the temperature increase by the MMW also depends on the size of the area. Thus, the factors such as the amplitude of the burst, the “averaging area” and the “averaging time” for the dosimetry would have to be considered.

Foster et al. [ 113 ] reviewed and modelled data on MMW-induced temperature increases in human skin. The model takes into account the frequencies of 3–100 GHz and smaller skin areas with the diameter of 1–2 cm. Available data on exposures lasting more than a few minutes, as well as areas of skin larger than 2 cm in diameter, were limited and made modeling difficult, but consistent with existing data. This means that this model, after appropriate evaluation for dosimetry, could use smaller areas of the skin. The authors also commented on the exposure guidelines for frequencies from 3 to 300 GHz in a separate article [ 114 ]. Based on “thermal modeling,” the authors considered the current guidelines to be conservative in terms of protection against temperature increases in the tissue. They also pointed out that the averaging time and average area provisions require further refinement and that the effects of short high intensity bursts may not be protected by the guidelines.

Zhadobov et al. [ 115 ] addressed the problem of accurate temperature measurement in in vitro MMW studies. They found that the type of thermal probe (thermocouples are better than fiber optic probes) and the size of the probe (smaller probes are more accurate) are relevant. In addition, they were able to show that the initial temperature rise during exposure is rapid (within seconds until a plateau is reached) and that the cells absorb very small amounts of energy, since most of the energy is already absorbed in the cell culture medium. Nevertheless, the authors have calculated that the exposure of 58.4 GHz with 10 mW/cm 2 leads to SAR values of more than 100 W/kg in a cell monolayer. This value is a fraction of the SAR values of the fluid surrounding the cells.

Several studies focused on the distribution of power density and the change in skin temperature as a result of exposure to MMW in the 6 to 100 GHz frequency range. The studies are experimental and/or modeling studies using previously published data. Alekseev et al. [ 116 , 117 ] investigated the absorption of the skin of mice and humans at frequencies between 30 and 82 GHz (10 mW/cm 2 ). They found that in both species absorption into both the epidermis and the dermis occurs with a concomitant loss of power density in the deeper regions. An extended study from the same group [ 118 ] on human forearm skin showed that both temperature increase and SAR values depend on frequency (in the interval of 25 to 75 GHz; 25, 73.3 and 128 mW/cm 2 ).

Frequency dependence for temperature increases was also observed in a modeling study with human facial skin [ 119 ]. Pulsed MMWs were used (6–100 GHz, 100 mW/cm 2 , 200–10,000 ms pulse length) and the skin temperatures were modeled as the function of both pulse length and frequency. Peak skin temperature increased as a function of frequency up to 20 GHz, while above 20 GHz it proved to be dependent on “absorption hotspots”. In deeper regions (>2 mm), the temperature increases were very low and highest around 10 GHz.

In addition, certain skin constituents have been shown to affect energy absorption. It has been shown that the presence of sweat glands [ 120 , 121 ] and also capillaries in the dermis can cause locally elevated SAR levels [ 122 ]. The latter study showed that SAR levels in vessels could be up to 30 times higher than in the surrounding skin, depending on the diameter of the vessels.

Both [ 23 ] and [ 123 ] have reported that the dielectric properties of different areas of the skin differ. The first study found that so-called acupuncture points in healthy volunteers show different dielectric properties when exposed to MMW (50–75 GHz, 14 mW/cm 2 ), while the second study even found differences between the epidermis and dermis (0–110 GHz).

These studies suggest that both the frequency and the specific condition and composition of the skin are relevant for tissue dosimetry. However, too few and very different studies are available to give a conclusive picture on dosimetry of 5G-relevant MMW exposures.

4.3. ICNIRP and other Exposure Recommendations

The guidelines for exposure limits for radiofrequency electromagnetic fields from 3 to 300 GHz in many countries are based on the recommendations of the International Commission on Non-Ionizing Radiation Protection (ICNIRP) [ 10 ]. However, there are also other organizations dealing with limit values such as the Institute of Electrical and Electronics Engineers, IEEE [ 11 ] or the US Federal Communications Commission, FCC [ 124 ].

The guidelines contain basic exposure limits that are indicated as SAR or power density. The limits for a given frequency differ only slightly, if at all, between the different guidelines. However, an important difference between the guidelines concerns frequency, as the SAR basic restriction values change to power density. This frequency (range) is currently set by ICNIRP at 10 GHz, while IEEE and FCC see this between 3–6 GHz. The current revision of these guidelines aims to harmonize these frequencies.

The exposure limits specified in the guidelines should protect against warming of tissue above 1 °C. The reason is that the perceived dangers of MMW energy are associated with excessive heating, called thermal effects. However, it must be considered that the guidelines mean a temperature increase of 1 °C relative to the starting temperature, regardless of the starting temperature. Elevations in temperature may cause pain in the skin when moderately increased, whereas at temperatures of 43–44 °C it may even induce burns [ 124 , 125 ].

At present, only thermal effects due to high-frequency electromagnetic fields are recognized as effects. This means that effects have a thermal component even if it is obviously not due to tissue that has been damaged by excessive heating. On the other hand, it has been suggested that the MMW exposure may also cause non-thermal effects. So far, however, no recognized expert committee has supported such an assertion.

4.4. Knowledge Gaps and Research Recommendations

Exposure of humans can occur through 5G devices with frequencies above 6 GHz, and may be primarily on the skin and, to a lesser extent, on the eyes. This is due to the very low penetration depth of this MMW. Therefore, it is important to investigate whether there are any health-related effects on the skin and/or effects associated with the skin. These include acute skin damage from tissue heating (burns), but possibly also less acute effects (such as inflammation, tumor development, etc.). Such effects could appear after prolonged and repeated heating of superficial structures (the skin). This would mean that thermal effects occur that are not due to acute but to chronic damage.

It may also be that local exposure causes energy deposition in the dermis of the skin, which may be so great as to affect nerve endings and peripheral blood vessels through warming mechanisms. Such scenarios were proposed by Ziskin [ 9 ] based on a series of studies by his group. These studies typically used exposures around 60 GHz at a power density of 10 mW/cm 2 on the skin in the sternum area to produce systemic effects. The aim was to treat certain diseases and complaints. The idea was that the treatment induces the release of the body’s own opioids and additionally stimulates the peripheral nerves. The stimulation would depend on a local thermal effect, which, due to the frequencies, induces locally high SAR values, even at low power densities, thus warming the tissue.

Due to the contradictory information from various lines of evidence that cannot be scientifically explained, and given the large gaps in knowledge regarding the health impact of MMW in the 6–100 GHz frequency range at relevant power densities for 5G, research is needed at many levels. It is important to define exact frequency ranges and power densities for possible research projects. There is an urgent need for research in the areas of dosimetry, in vivo dose-response studies and the question of non-thermal effects. It is therefore recommended that the following knowledge gaps should be closed by appropriate research (the list of research recommendations is not prioritized):

• Exact dosimetry with consideration of the skin for relevant frequency ranges, including the consideration of short intense pulses (bursts)
• Studies on inflammatory reactions starting from the skin and the associated tissues
• In vivo studies on the influence of a possible tissue temperature increase (e.g., nude mouse or hairless mouse model)
• In vivo dose-response studies of heat development
• Use of in vitro models (3D models) of the skin for molecular and cellular endpoints
• Clarification of the question about non-thermal effects (in vitro)

There are also questions about the environmental impact, with potential consequences for human health. Since many MMW devices will be installed in the environment, the impact of MMW on insects, plants, bacteria, and fungi is relevant to investigate. Particularly relevant is the question of temperature increase in very small organisms, as the depth of penetration of the MMW could warm the whole organism.

An unrealistic scenario, however, is that MMW exposures at realistic power densities could cause systemic body warming in humans. Any local heat exposure would be dissipated by the body’s normal heat regulation system. This is mainly due to convection caused by blood flow adjacent to the superficial skin areas where the actual exposure takes place.

In summary, it should be noted that there are knowledge gaps with respect to local heat developments on small living surfaces, e.g., on the skin or on the eye, which can lead to specific health effects. In addition, the question of any possibility of non-thermal effects needs to be answered.

5. Conclusions

Since the ranges up to 30 GHz and over 90 GHz are sparingly represented, this review mainly covers studies done in the frequency range from 30.1 to 65 GHz.

In summary, the majority of studies with MMW exposures show biological responses. From this observation, however, no in-depth conclusions can be drawn regarding the biological and health effects of MMW exposures in the 6–100 GHz frequency range. The studies are very different and the total number of studies is surprisingly low. The reactions occur both in vivo and in vitro and affect all biological endpoints studied.

There does not seem to be a consistent relationship between intensity (power density), exposure time, or frequency, and the effects of exposure. On the contrary, and strikingly, higher power densities do not cause more frequent responses, since the percentage of responses in most frequency groups is already at 70%. Some authors refer to their study results as having “non-thermal” causes, but few have applied appropriate temperature controls. The question therefore remains whether warming is the main cause of any observed MMW effects?

In order to evaluate and summarize the 6–100 GHz data in this review, we draw the following conclusions:

• Regarding the health effects of MMW in the 6–100 GHz frequency range at power densities not exceeding the exposure guidelines the studies provide no clear evidence, due to contradictory information from the in vivo and in vitro investigations.
• Regarding the possibility of “non-thermal” effects, the available studies provide no clear explanation of any mode of action of observed effects.
• Regarding the quality of the presented studies, too few studies fulfill the minimal quality criteria to allow any further conclusions.

Supplementary Materials

The following are available online at https://www.mdpi.com/1660-4601/16/18/3406/s1 , Table S1: Master-table of the selected (in vivo and in vitro) studies and the extracted physical, biological, and quality parameters.

Author Contributions

M.S. and M.-O.M. have contributed equally to conceptualization, structuring, data collection and analysis, interpretation of data, and all aspects of writing of the manuscript.

This research was funded by Deutsche Telekom Technik GmbH, Bonn, Germany, PO number 4806344812.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Fifth Generation Antennas: A Comprehensive Review of Design and Performance Enhancement Techniques

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