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This study introduces a low-cost alternative method for mapping the electric field strength from 4G LTE base stations and identifies areas where this mapping is more accurate. A drive test campaign was conducted in the urban environment of Thessaloniki, Greece, using data obtained from three identical smartphones, each connected to a different mobile operator and an exposimeter. The smartphones used a mobile application to record Reference Signal Received Power (RSRP) values, while the exposimeter measured the electric field strength in selected frequency bands. In the first part, the variability of the received power over different periods within certain areas was studied, and the reasons for this variability were identified. In the second part, a linear factor was calculated to convert RSRP values into electric field strength using data from both the application and the exposimeter. The converted RSRP values were subsequently compared with the exposimeter data for validation. The results indicate that in areas where the variability of the received power is lower, the linear relationship between smartphone and exposimeter data is statistically stronger resulting in calculated electric field strength values are closer to the measured. [ABSTRACT FROM AUTHOR]

This study presents the measurements of exposure to electromagnetic fields, carried out comparatively following standard methods from fixed sites using a broadband meter and using a smartphone on which an App designed for this purpose has been installed. The results of two measurement campaigns carried out on the campus of the University of Alcalá over an area of 1.9 km2 are presented. To characterize the exposure, 20 fixed points were measured in the first case and 860 points along the route made with a bicycle in the last case. The results obtained indicate that there is proportionality between the two methods, making it possible to use the smartphone for comparative measurements. The presented methodology makes it possible to characterize the exposure in the area under study in four times less time than that required with the traditional methodology. [ABSTRACT FROM AUTHOR]

In this presented study, we measured in situ the uplink duty cycles of a smartphone for 5G NR and 4G LTE for a total of six use cases covering voice, video, and data applications. The duty cycles were assessed at ten positions near a 4G and 5G base-station site in Belgium. For Twitch, VoLTE, and WhatsApp, the duty cycles ranged between 4% and 22% in time, both for 4G and 5G. For 5G NR, these duty cycles resulted in a higher UL-allotted time due to time division duplexing at the 3.7 GHz frequency band. Ping showed median duty cycles of 2% for 5G NR and 50% for 4G LTE. FTP upload and iPerf resulted in duty cycles close to 100%. [ABSTRACT FROM AUTHOR]

This study introduces a low-cost alternative method for mapping the electric field strength from 4G LTE base stations and identifies areas where this mapping is more accurate. A drive test campaign was conducted in the urban environment of Thessaloniki, Greece, using data obtained from three identical smartphones, each connected to a different mobile operator and an exposimeter. The smartphones used a mobile application to record Reference Signal Received Power (RSRP) values, while the exposimeter measured the electric field strength in selected frequency bands. In the first part, the variability of the received power over different periods within certain areas was studied, and the reasons for this variability were identified. In the second part, a linear factor was calculated to convert RSRP values into electric field strength using data from both the application and the exposimeter. The converted RSRP values were subsequently compared with the exposimeter data for validation. The results indicate that in areas where the variability of the received power is lower, the linear relationship between smartphone and exposimeter data is statistically stronger resulting in calculated electric field strength values are closer to the measured.

Exposure to the Electromagnetic Fields (EMF) generated from cellular antennas is a topic of importance, and even more so since the arrival of 5G and the promise of a future with denser deployments. In this paper, we describe the planning and execution of EMF measurements in Luxembourg and the lessons learned from that process. We describe the specifics of Luxembourg, how the pilot sites as well as the measuring devices have been selected. We also discuss the results of the measurements from fixed and mobile devices, with regard to the regulatory limits. Finally, we describe the facts that limit the short-term deployment of devices and the difficulties to measure 5G exposition. All the datasets collected for this study are proposed as open-source format.

All plants, including ornamentals, are subject to different stressors related to their environment. These can disrupt their progress, including their ability to generate pollen and reproduce successfully. These stressors may involve inert natural impacts such as temperature, deficiency and salinity levels of water. They may also involve natural active effects such as herbivores and pathogens. Other types of accidental natural effects, such as storms and lightning, could also occur. There are also artificial effects that shape the environment of human activity. Nowadays, the environment of electromagnetic fields, and in particular those at high frequency, are an important element. This contribution aims to propose an analysis and a strategy for controlling the biological effects of plant exposure to such fields. The analysis takes into account the nature of the exposure source, the properties of the exposed materials and the exposure conditions. This is accomplished through the governing equations related to electromagnetic and heat transfer phenomena permitting the prediction of biological thermal effects of the exposure. The involved coupled phenomena solution approach makes it possible to predict, verify, and provide means of protection against exposure. The proposed survey is supported by a review of the literature on the various subjects concerned.

When performing a radio frequency (RF) electromagnetic field (EMF) exposure assessment of a base station as described in the international standard IEC 62232, the actual maximum approach provides an assessment method based on the actual exposure level, in particular for massive MIMO base stations. Computational modeling can be used to estimate a range of applicable power reduction factors. To date, research studies have generally focused on the channel modeling of actual RF EMF exposure assuming that the attached user equipment (UE) is static. However, in real operational conditions, a UE can be moving and triggering multiple beam changes or beam adaptations. This study provides a computational model applicable to moving UEs and investigates the impact on range of applicable power reduction factors compared to modelling studies using static UEs. The results show that -1.5 dB to -3.5 dB lower power reduction factor can be considered with moving UEs compared to static UEs.

As part of the process for monitoring public exposure to electromagnetic waves, the national frequency Agency is carrying out, in collaboration with the Ministry of Ecological Transition and Territorial Cohesion, the Scientific and Technical Center for Building (CSTB) and Geomod, a numericalmodeling of the electromagnetic wave exposure levels emitted by mobile telephony base stations on a national scale. This paper presents a dedicated simulation method for the numerical modeling of the whole French territory's exposure to EMF. This method accounts for EMF exposure everywhere (outdoors and inside buildings), while performing fast enough to fulfill operational constraints. The simulation method relies on a ray-based 2.5D and 3Dmixed approach that takes into account computation areas depending on the radiated power pattern of the antennas. Themethod is yet deployed on pilot areas before a full deployment. [ABSTRACT FROM AUTHOR]

This contribution aims to analyze compliance with the rules relating to disturbances in the domain of health due to exposure to electromagnetic fields (EMF). This concerns safety standards for exposed living tissue and the integrity of exposed medical devices acting on the body. This investigation is carried out by reviewing and analyzing these exposure effects. In the paper, the EMF exposure, the nature of sources and the characters of their interactions with objects are first illustrated. Then, EMF exposure restrictions accounting for living tissues safety standards as well as medical devices constancy are discussed. Exposure biological effects comprising both thermal and non-thermal effects are then detailed. The verification and control of EMF effects are next illustrated including mathematical modeling of EMF effects, governing equations and body tissues representation in the solution of these equations. At the end of the paper, two examples representing the cases of tissues and devices are given to check the rules under exposure to EMF: biological effects on exposed human tissues and integrity of a magnetic resonance imager under external disturbance.

New wireless technologies significantly utilize the spectrum around 6 GHz with some of them, like Wi-Fi®6E, using both the spectrum below and above 6 GHz. At these frequencies, the main challenge for electromagnetic field (EMF) exposure assessments is due to the exposure metric changing from specific absorption rate (SAR) to absorbed power density (APD). Moreover, due to current measurement limitations, the incident power density (IPD) rather than APD is used in practice. In this context, the maximum allowed output power to ensure exposure compliance is dependent on the metric used and can lead to a discontinuity below and above 6 GHz even for different channels of the same technology. This paper studies such a discontinuity at the transition frequency of 6 GHz using a dipole antenna and a Planar Inverted F Antenna (PIFA). The study was performed at several exposure distances by means of numerical simulations as well as experimental measurements. The assessment was based on the comparison between maximum power values obtained while remaining compliant to the SAR and IPD limits for the same exposure conditions. The results have shown that for a specific source there was a distance (between 5 and 10 mm) where the highest power reduction for compliance switched from SAR to IPD. The difference or discontinuity level varied between 2 and 6 dB depending on the exposure distance and the source. In summary, SAR is more restrictive at closer distances, while the IPD induces a higher back-off power with an increase in distance.

To provide enhanced mobile services, the 5G system is expected to further densify its network infrastructure and scale up the deployment of massive antenna arrays that emit high-energy beams using the millimeter wave spectrum. These radically new features will significantly impact the EMF exposure level in the 5G networks. In this paper, EMF exposure for 5G mobile networks in a dense urban environment is investigated using a raytracing approach for the uplink (UL) and downlink (DL). A massive multi-input multi-output antenna with multiuser beamforming capability is considered for the 5G base station. For DL, the maximum rate transmission (MRT) technique is used to direct the beams toward all the active users, and total power density (PD) is used to evaluate the EMF exposure level. On the other hand, EMF exposure due to UL is investigated using electric field strength and specific absorption rate (SAR). The proposed ray-tracing based EMF evaluation framework exploits detailed information of the scenarios, including 3D building geometry, EM characteristics, multipath propagation, user locations and beamforming radiation pattern, to effectively evaluate the EMF’s spatial variation levels. Following this evaluation procedure, the impact of different user densities and distributions is analyzed in terms of PD and SAR. Results show that for DL, the peak PD increases from 6.65 to 24.92 dBm/m2 when the number of active users in the area increases from a single user to 100%. Considering the worst-case scenario, the PD exposure reaches 62% of the ICNIRP’s limit. Saturation of the spatial EMF distribution occurs when the number of active DL beams is above 25%. For UL, within 5m radius of the user’s location, the average E-field may increase from 2.40 to 3.98 V/m. (increment of 66%) if the number of active users in the area increases from 25% to 100%. Moreover, when 100% of the users are actively transmitting, there is only a 10% probability that the SAR may exceed 0.06 W/kg (or 3% of the ICNIRP’s limit).

This contribution aims to analyze compliance with the rules relating to disturbances in the domain of health due to exposure to electromagnetic fields (EMF). This concerns safety standards for exposed living tissue and the integrity of exposed medical devices acting on the body. This investigation is carried out by reviewing and analyzing these exposure effects. In the paper, the EMF exposure, the nature of sources and the characters of their interactions with objects are first illustrated. Then, EMF exposure restrictions accounting for living tissues safety standards as well as medical devices constancy are discussed. Exposure biological effects comprising both thermal and non-thermal effects are then detailed. The verification and control of EMF effects are next illustrated including mathematical modeling of EMF effects, governing equations and body tissues representation in the solution of these equations. At the end of the paper, two examples representing the cases of tissues and devices are given to check the rules under exposure to EMF: biological effects on exposed human tissues and integrity of a magnetic resonance imager under external disturbance. [ABSTRACT FROM AUTHOR]

The NB-IoT (NarrowBand-Internet of Things) radio technology is now widely implemented by mobile phone network operators to support the communication of IoT devices such as smart meters, insurance black boxes for cars, network connected waste bins, smart bicycles. In the present work, some LTE800 cells of different mobile phone network operators implementing the NB-IoT technology in the guard band mode have been investigated. The signals, consisting of a PRB (Physical Resource Block) 180 kHz wide, have been analyzed and characterized in the time domain by means of a narrow band instrumental chain equipped with a Rohde & Schwarz FSH8 spectrum analyzer. Time domain analysis allows us to identify, within the transmission frame, the position of the NB-IoT signaling channels such as the Narrowband Reference Signal (NRS), the primary (NPSS) and secondary (NSSS) synchronization signals and the broadcast channel (NPBCH), but, above all, to measure the power received during the transmission of the NRS. This value has been compared with that measured by the NB-IoT decoding module supplied on the same analyzer, in order to verify the equivalence of these measurement methods. This would allow use of a more diffuse and cheaper instrumentation rather than more expensive vector analyzers, currently required to assess electric fields due to the NB-IoT signals through the extrapolation techniques set by Italian CEI 211-7/E technical standard. [ABSTRACT FROM AUTHOR]

In recent years, the development of wireless technologies has led to fast growth in mobile networks, especially with the rise of 5G New Radio (5G NR). A huge number of base stations (BSs) are mandatory to serve the growth of mobile services, which has led to concerns about the increase in electromagnetic field (EMF) radiation exposure levels. To control the overall power emitted by EMF transmitters, international bodies have set maximum exposure limits. This paper investigates the compliance distances (CDs) of shared sites by a group of Mobile Network Operators (MNO) as multi-operators operating with multi-technology and sharing the same tower. The study investigated the CDs of the most two commonly used types of sharing sites, macro and indoor-Based solution sites (IBS). In addition, the study analyzed the power densities and total exposure ratios for the general public and occupational workers in each sharing scenario. The results showed that, compared with a single MNO, the CD increased by 41% in the case of two MNOs, 73% for three MNOs, and 100% for four MNOs. The EMF site sharing scale-up formula was used to estimate the increase in CDs for N number of MNOs assuming that all MNOs use the same site configuration. In addition, the results showed that 5G has the highest contribution to the total exposure ratio (TER) at the CD in the main direction of the antennae. [ABSTRACT FROM AUTHOR]

In this paper, we exploit the artificial neural network (ANN) model for a spatial reconstruction of radio-frequency (RF) electromagnetic field (EMF) exposure in an outdoor urban environment. To this end, we have carried out a drive test measurement campaign covering a large part of Paris, along a route of approximately 65 Km. The electric (E) field strength has been recorded over a wide band ranging from 700 to 2700 MHz. From these measurement data, the E-field strength is extracted and computed for each frequency band of each telecommunication operator. First, the correlation between the E-fields at different frequency bands is computed and analyzed. The results show that a strong correlation of E-field levels is observed for bands belonging to the same operator. Then, we build ANN models with input data encompassing information related to distances to N neighboring base stations (BS), receiver location and time variation. We consider two different models. The first one is a fully connected ANN model, where we take into account the N nearest BSs ignoring the corresponding operator. The second one is a hybrid model, where we consider locally connected blocks with the N nearest BSs for each operator, followed by fully connected layers. The results show that the hybrid model achieves better performance than the fully connected one. Among N∈{3,5,7}, we found out that with N=3, the proposed hybrid model allows a good prediction of the exposure level while the maintaining acceptable complexity of the model.

With the ongoing fifth-generation cellular network (5G) deployment, electromagnetic field exposure has become a critical concern. However, measurements are scarce, and accurate electromagnetic field reconstruction in a geographic region remains challenging. This work proposes a conditional generative adversarial network to address this issue. The main objective is to reconstruct the electromagnetic field exposure map accurately according to the environment's topology from a few sensors located in an outdoor urban environment. The model is trained to learn and estimate the propagation characteristics of the electromagnetic field according to the topology of a given environment. In addition, the conditional generative adversarial network-based electromagnetic field mapping is compared with simple kriging. Results show that the proposed method produces accurate estimates and is a promising solution for exposure map reconstruction. [ABSTRACT FROM AUTHOR]

To provide enhanced mobile services, the 5G system is expected to further densify its network infrastructure and scale up the deployment of massive antenna arrays that emit highenergy beams using the millimeter wave spectrum. These radically new features will significantly impact the EMF exposure level in the 5G networks. In this paper, EMF exposure for 5G mobile networks in a dense urban environment is investigated using a raytracing approach for the uplink (UL) and downlink (DL). A massive multi-input multi-output antenna with multiuser beamforming capability is considered for the 5G base station. For DL, the maximum rate transmission (MRT) technique is used to direct the beams toward all the active users, and total power density (PD) is used to evaluate the EMF exposure level. On the other hand, EMF exposure due to UL is investigated using electric field strength and specific absorption rate (SAR). The proposed ray-tracing based EMF evaluation framework exploits detailed information of the scenarios, including 3D building geometry, EM characteristics, multipath propagation, user locations and beamforming radiation pattern, to effectively evaluate the EMF's spatial variation levels. Following this evaluation procedure, the impact of different user densities and distributions is analyzed in terms of PD and SAR. Results show that for DL, the peak PD increases from 6.65 to 24.92 dBm/m2 when the number of active users in the area increases from a single user to 100%. Considering the worst-case scenario, the PD exposure reaches 62% of the ICNIRP's limit. Saturation of the spatial EMF distribution occurs when the number of active DL beams is above 25%. For UL, within 5m radius of the user's location, the average E-field may increase from 2.40 to 3.98 V/m. (increment of 66%) if the number of active users in the area increases from 25% to 100%. Moreover, when 100% of the users are actively transmitting, there is only a 10% probability that the SAR may exceed 0.06 W/kg (or 3% of the ICNIRP's limit). [ABSTRACT FROM AUTHOR]

In this paper, we exploit the artificial neural network (ANN) model for a spatial reconstruction of radio-frequency (RF) electromagnetic field (EMF) exposure in an outdoor urban environment. To this end, we have carried out a drive test measurement campaign covering a large part of Paris, along a route of approximately 65 Km. The electric (E) field strength has been recorded over a wide band ranging from 700 to 2700 MHz. From these measurement data, the E-field strength is extracted and computed for each frequency band of each telecommunication operator. First, the correlation between the E-fields at different frequency bands is computed and analyzed. The results show that a strong correlation of E-field levels is observed for bands belonging to the same operator. Then, we build ANN models with input data encompassing information related to distances to N neighboring base stations (BS), receiver location and time variation. We consider two different models. The first one is a fully connected ANN model, where we take into account the N nearest BSs ignoring the corresponding operator. The second one is a hybrid model, where we consider locally connected blocks with the N nearest BSs for each operator, followed by fully connected layers. The results show that the hybrid model achieves better performance than the fully connected one. Among N ∈ { 3 , 5 , 7 } , we found out that with N = 3 , the proposed hybrid model allows a good prediction of the exposure level while the maintaining acceptable complexity of the model. [ABSTRACT FROM AUTHOR]

This work considers the problem of energy efficiency (EE) maximization in a reconfigurable intelligent surface (RIS)-aided multiple input multiple output (MIMO) communication link, subject to maximum power constraints and to additional constraints on the maximum exposure of the end-users to electromagnetic radiations. The RIS phase shifts, the transmit beamforming, the linear receive filter, and the transmit power are jointly optimized, and two provably convergent and low-complexity algorithms are developed. One algorithm applies to the general system setup, but does not guarantee global optimality. The other is provably optimal in the notable special case of isotropic electromagnetic field (EMF) exposure constraints. The numerical results show that an RIS ensures an EE of the same order of magnitude as when no EMF constraints are enforced. [ABSTRACT FROM AUTHOR]

In this paper, exposure induced in the vicinity of four pilot sites with 5G NR antennas in the 3.4–3.8 GHz band is assessed in-situ. Different manufacturers of antennas and different types of antenna are considered. Measurements are performed without any traffic, with continuous traffic in one direction and with on demand download of files. These measurements highlighted the variation in the level of exposure depending on use and led to the proposal of a new indicator to calculate the actual exposure created by 5G networks with steerable beams. This indicator results in a reduction factor that is used to assess the exposure in live conditions based on the configured maximum antenna power.

Two outdoor base station macrocell/microcell topologies in operational Global System for Mobile communications (GSM) and Universal Mobile Telecommunications Service (UMTS) networks are compared with respect to average Electromagnetic Field (EMF) exposure over population in an area. A novel joint metric is used, accounting for exposure from both base stations and user equipment. The demonstrated method tends to use as much data as possible that can be extracted from various network systems, for the exact time of measurements or on long-term basis, with the aim of identifying the potential for EMF-awareness of future networks. The reduction of total exposure with the introduction of the microcell layer is shown using the proposed method with experimental measurements and compared by mobile network technologies. The introduction of the micro layer brought reduction to total population exposure of 84.6%, in the micro base station coverage area, mostly due to user device exposure reduction in GSM. UMTS user device exposure reduction was even more pronounced, 97.8%, but having less impact on overall exposure, contributing only 1%. Even with the increase in exposure originating from base stations, the reduction of total exposure was visible over the macro area as well, measuring 2.22%. The uncertainties of the evaluation method are identified and usage of advanced tools and methods is proposed to mitigate them.

The deployment of the fifth-generation (5G) wireless communication services requires the installation of 5G next-generation Node-B Base Stations (gNBs) over the territory and the wide adoption of 5G User Equipment (UE). In this context, the population is concerned about the potential health risks associated with the Radio Frequency (RF) emissions from 5G equipment, with several communities actively working toward stopping the 5G deployment. To face these concerns, in this work, we analyze the health risks associated with 5G exposure by adopting a new and comprehensive viewpoint, based on the communications engineering perspective. By exploiting our background, we investigate the alleged health effects of 5G exposure and critically review the latest works that are often referenced to support the health concerns from 5G. We then precisely examine the up-to-date metrics, regulations, and assessment of compliance procedures for 5G exposure, by evaluating the latest guidelines from the Institute of Electrical and Electronics Engineers (IEEE), the International Commission on Non-Ionizing Radiation Protection (ICNIRP), the International Telecommunication Union (ITU), the International Electrotechnical Commission (IEC), and the United States Federal Communications Commission (FCC), as well as the national regulations in more than 220 countries. We also thoroughly analyze the main health risks that are frequently associated with specific 5G features (e.g., multiple-input multiple-output (MIMO), beamforming, cell densification, adoption of millimeter waves, and connection of millions of devices). Finally, we examine the risk mitigation techniques based on communications engineering that can be implemented to reduce the exposure from 5G gNB and UE. Overall, we argue that the widely perceived health risks that are attributed to 5G are not supported by scientific evidence from communications engineering. In addition, we explain how the solutions to minimize the health risks from 5G (including currently unknown effects) are already mature and ready to be implemented. Finally, future works, e.g., aimed at evaluating long-term impacts of 5G exposure, as well as innovative solutions to further reduce the RF emissions, are suggested.

This paper reports the electromagnetic field (EMF) exposure levels from fifth generation (5G) services. Three mobile operators in South Korea launched the world's first 5G New Radio networks using the 3.5 GHz band in April 2019. The transmitted power of the uplink slots and the synchronization signal reference signal received power (SS-RSRP) from user equipment (UE) were measured in Seoul. The power samples, averaged over a 1-s duration, were obtained for a traffic period of approximately 270 h from October 2019 to early February 2020 using the file transfer protocol while driving along the side streets in residential areas of Seoul. The measurement results show that the time-average level when exposed to a beam sweep of the base stations was less than 5 μW/m2. However, the UE transmitted power level approached the maximum for a considerable period of the total measurement time owing to the extremely low SS-RSRP level of the base stations.

An exposure system was designed and implemented for the purpose of joint large-scale animal experiments conducted in Korea and Japan using a reverberation chamber (RC) in both countries. Prior to the start of the animal experiments, the parameters S21, electric field (E-field) uniformity, and Q factor were evaluated to confirm the performance of the developed chambers. The E-field uniformity, which is the most important performance factor of an RC, was evaluated at 900 MHz on 150 measurement values taken at 150 points in a loaded chamber with 80 live rats and in an empty chamber. The conditions of the loaded chamber with the rats are almost the same as the actual experimental environment and in which the rats, watering systems, animal bedding, cages, and cage racks were included. Two mean body weights of 330 and 470 g for the 80 rats were considered. The E-field uniformity was within the mean ± 1.0 dB and mean ± 2.3 dB under the empty and the rat-loaded conditions, respectively.

The NB-IoT (NarrowBand-Internet of Things) radio technology is now widely implemented by mobile phone network operators to support the communication of IoT devices such as smart meters, insurance black boxes for cars, network connected waste bins, smart bicycles. In the present work, some LTE800 cells of different mobile phone network operators implementing the NB-IoT technology in the guard band mode have been investigated. The signals, consisting of a PRB (Physical Resource Block) 180 kHz wide, have been analyzed and characterized in the time domain by means of a narrow band instrumental chain equipped with a Rohde & Schwarz FSH8 spectrum analyzer. Time domain analysis allows us to identify, within the transmission frame, the position of the NB-IoT signaling channels such as the Narrowband Reference Signal (NRS), the primary (NPSS) and secondary (NSSS) synchronization signals and the broadcast channel (NPBCH), but, above all, to measure the power received during the transmission of the NRS. This value has been compared with that measured by the NB-IoT decoding module supplied on the same analyzer, in order to verify the equivalence of these measurement methods. This would allow use of a more diffuse and cheaper instrumentation rather than more expensive vector analyzers, currently required to assess electric fields due to the NB-IoT signals through the extrapolation techniques set by Italian CEI 211-7/E technical standard.

International radio frequency (RF) electromagnetic field (EMF) exposure assessment standards and regulatory bodies have developed methods and specified requirements to assess the actual maximum RF EMF exposure from radio base stations enabling massive multiple-input multiple-output (MIMO) and beamforming. Such techniques are based on the applications of power reduction factors (PRFs), which lead to more realistic, albeit conservative, exposure assessments. In this study, the actual maximum EMF exposure and the corresponding PRFs are computed for a millimeter-wave radio base station array antenna. The computed incident power densities based on near-field and far-field approaches are derived using a Monte Carlo analysis. The results show that the actual maximum exposure is well below the theoretical maximum, and the PRFs similar to those applicable for massive MIMO radio base stations operating below 6 GHz are also applicable for millimeter-wave frequencies. Despite the very low power levels that currently characterize millimeter-wave radio base stations, using the far-field approach can also guarantee the conservativeness of the PRFs used to assess the actual maximum exposure close to the antenna.

The deployment of the 5th-generation cellular networks (5G) and beyond has triggered health concerns due to the electric and magnetic fields (EMF) exposure. In this letter, we propose a novel architecture to minimize the population exposure to EMF by considering a smart radio environment with a reconfigurable intelligent surface (RIS). Then, we optimize the RIS phases to minimize the exposure in terms of the exposure index (EI) while maintaining a minimum target quality of service. The proposed scheme achieves up to 20% reduction in EI compared to schemes without RISs. [ABSTRACT FROM AUTHOR]

Paving the path toward the fifth generation (5G) of wireless networks with a huge increase in the number of user equipment has strengthened public concerns on human exposure to radio-frequency electromagnetic fields (RF EMFs). This requires an assessment and monitoring of RF EMF exposure, in an almost continuous way. Particular interest goes to the uplink (UL) exposure, assessed through the transmission power of the mobile phone, due to its close proximity to the human body. However, the UL transmit (TX) power is not provided by the off-the-shelf modem and RF devices. In this context, we first conduct measurement campaigns in a multi-floor indoor environment using a drive test solution to record both downlink (DL) and UL connection parameters for Long Term Evolution (LTE) networks. Several usage services (including WhatsApp voice calls, WhatsApp video calls, and file uploading) are investigated in the measurement campaigns. Then, we propose an artificial neural network (ANN) model to estimate the UL TX power, by exploiting easily available parameters such as the DL connection indicators and the information related to an indoor environment. With those easy-accessed input features, the proposed ANN model is able to obtain an accurate estimation of UL TX power with a mean absolute error (MAE) of 1.487 dB.

This paper describes the current science-based approach to ensuring public safety from RF-EMF base stations. It acknowledges that a degree of public concern persists despite the fact that dose limits are seldom if ever approached in practice. One plausible contributor to the discord is a tendency within parts of academia and by some planning authorities to pursue a technocratic policy approach to siting wherein public concerns are attributed to scientific uncertainty over health risks, whereas the reality is that societal concerns over base stations is broader. Thus, potential mis-framing of the debate as a purely scientific issue leads to inappropriate risk communication exercises which in fact polarise the situation by disenfranchising other potentially legitimate siting concerns. It is recommended that more attention should be paid to the non-health related siting issues, which could be handled by a thoughtful democratic / deliberative process, and that this should not be conflated with the scientific debate over the uncertain and possibly non-existent risks posed by RF EMF complying with the existing science-based dose limits.

The design of a massive MIMO network requires a channel model that captures the Spatio-temporal dimensions of the propagation environment. In this paper, we propose a novel method combining Hybrid Raytracing - Finite difference time domain (FDTD) and network planner tools to address this requirement. This method provides accurate and realistic EMF exposure models for the design of a massive MIMO network. Using this method, we proceed with the optimization of the BS's locations under the low power consumption and low EMF exposure constraints. Assuming equal preference of the optimization objectives, the simulations show that the uplink localized 10g dose appears to be the dominant factor of the localized 10g EMF exposure. Moreover, a massive MIMO network designed to serve 224 simultaneous active users at the same time-frequency resource is subject to an increase of the total whole-body dose (2 times higher in downlink and +18% in uplink), compared to a design with 14 active users. However, in the same conditions, the downlink localized 10g dose reduces (20 times lower) whereas the uplink localized 10g dose increases (+23%) in comparison with the scenario with fewer users (14). Besides, the electromagnetic field strength in all locations obtained with this new method is 2 times weaker compared to a 4G LTE network, while complying with the international guidelines.

This paper presents a numerical approach for massive multiple-input multiple-output (MIMO) human exposure assessment. It combines ray-tracing for the estimation of the wireless channel and the finite-difference time-domain method to simulate the exposure of a realistic human phantom. We apply it to estimate the exposure in a model of an industrial indoor environment with a single massive MIMO base station (BS). The exposure scenarios include line-of-sight and non-line-of-sight propagation with the BS using equal gain transmission precoding at 3.5 GHz. Calculated channel parameters are discussed in comparison with the data available in the literature. The exposure in the phantom's head is evaluated in terms of the peak-spatial specific absorption rate averaged over a 10-g cube and referenced to the free-space time-averaged Poynting vector magnitude at the same location.

Advanced antenna technology in the form of massive multiple input multiple output (mMIMO) antennas has been deployed in fourth generation (4G) long term evolution (LTE) mobile networks and will be a standard feature in fifth generation (5G) networks. A characteristic of mMIMO is beamforming in which a large array of antenna elements is used to concentrate energy in specific narrow directions to improve data throughput. Assessing the electromagnetic field (EMF) compliance boundary around a beamforming capable mMIMO antenna using a traditional approach that assumes maximum power is simultaneously transmitted in every possible direction and the radio base station (RBS) is fully loaded (100% traffic utilization) may produce very conservative results. In this study we report on measurements of the 6-minute time-averaged EMF levels in front of a mMIMO antenna operating in a 4G LTE time division duplex (TDD) network and compare results with conservatively computed EMF levels. The RBS serves users scattered throughout a dense urban environment characterized by low rise commercial/industrial buildings. When scaled to 100% RBS traffic loading and taking TDD operation into account, the highest measured EMF level was 7.3% to 16.1% of the ICNIRP occupational reference level compared to a conservative computed level of 79.3%. This represents a far-field reduction in the occupational compliance boundary of between 2.2 and 3.3 times and is consistent with other statistically based theoretical studies. An additional reduction in the compliance boundary can be expected due to actual RBS traffic loading often being much less than 100%.

This work is situated at the conjunction of the fields of distributed systems, telecommunications, and mathematical modeling, aiming to offer solutions to the problem of people’s overexposure to electro-magnetic fields (EMF) radiation. In this paper, we propose a new routing scheme for wireless multi-hop networks, which seeks a fairer distribution of the exposure to electromagnetic fields, by leveraging a combination of the transmitted power and the accumulated exposure as a routing metric. We carry out a holistic approach, including: (1) an algorithmic study, (2) an analytical model of the aforementioned novel routing metric, and (3) the specification of a routing protocol. We make a performance assessment of our novel routing protocol and the corresponding algorithm, by means of an extensive simulation campaign over the NS-3 simulator. The obtained results yield that the proposed novel solution is able to not only fairly distribute the exposure, but also to reduce its average value, thus enhancing the user experience. We also show that the power consumption using the EMF-aware proposed solution, based on Cycle Canceling Algorithm (CCA), and that observed with an approach seeking power reduction are alike. Indeed, even if there exist key-differences from the user experience’s point of view between both routing approaches, there is no statistically relevant power increase between them. Thus, our solution manages to keep the consumed power at a low level, and at the same time it reduces the overall nodes’ exposure to EMF.

Featured Application: The presented numerical approach can be directly applied to the estimation of the compliance boundary of the antenna array base stations and the downlink human EMF exposure assessment in the networks served by such base stations. In the near future, wireless coverage will be provided by the base stations equipped with dynamically-controlled massive phased antenna arrays that direct the transmission towards the user. This contribution describes a computational method to estimate realistic maximum power levels produced by such base stations, in terms of the time-averaged normalized antenna array gain. The Ray-Tracing method is used to simulate the electromagnetic field (EMF) propagation in an urban outdoor macro-cell environment model. The model geometry entities are generated stochastically, which allowed generalization of the results through statistical analysis. Multiple modes of the base station operation are compared: from LTE multi-user codebook beamforming to the more advanced Maximum Ratio and Zero-Forcing precoding schemes foreseen to be implemented in the massive Multiple-Input Multiple-Output (MIMO) communication protocols. The influence of the antenna array size, from 4 up to 100 elements, in a square planar arrangement is studied. For a 64-element array, the 95th percentile of the maximum time-averaged array gain amounts to around 20% of the theoretical maximum, using the Maximum Ratio precoding with 5 simultaneously connected users, assuming a 10 s connection duration per user. Connection between the average array gain and actual EMF levels in the environment is drawn and its implications on the human exposure in the next generation networks are discussed. [ABSTRACT FROM AUTHOR]

This study presents a research category classification method for scientific literature on the human health risk of electromagnetic fields. The proposed method uses the document embedding model, Doc2Vec, to convert the research article text data into a vector, through which it trains three binary classifiers to determine whether the article belongs to animal experiments, cell experiments, or epidemiological studies. Finally, by using the trained binary classifiers, the research articles were automatically classified into one of three research categories. The proposed method was implemented for performance evaluation with 120 research articles on the human health risk of electromagnetic fields. Among the 120 research articles, 90 were used as a training dataset, while 30 were used as a test dataset. The implementation results showed that the proposed method can classify the research articles on the human health risk of electromagnetic fields with 88% accuracy on average. [ABSTRACT FROM AUTHOR]

In this work, monitoring of the transmit power for several base stations operating in a live 5G network (Telstra, Australia) was conducted with the purpose of analyzing the radio frequency (RF) electromagnetic field (EMF) exposure levels. The base stations made use of state-of-the-art massive MIMO antennas utilizing beamforming in order to optimize the signal strength at the user's device. In order to characterize the actual EMF exposure from 5G base stations, knowledge of the amount of power dynamically allocated to each beam is therefore of importance. Experimental data on the spatial distribution of the base stations' transmit power were gathered directly from the network by extracting information on the radio and baseband operations. Out of more than 13 million samples collected over 24 h, the maximum time-averaged power per beam direction was found to be well-below the theoretical maximum and lower than what was predicted by the existing statistical models. The results show that assuming constant peak power transmission in a fixed beam direction leads to an unrealistic EMF exposure assessment. This work provides insights relevant for the standardization of EMF compliance assessment methodologies applicable for 5G base stations. [ABSTRACT FROM AUTHOR]

Introduction. Mobile phones are worldwide spread nowadays. Smartphones penetration is growing year after year. Numerous studies indicate the negative effect of EMF exposure of these devices on humans. Therefore, it is important to study the peculiarities of their influence on the target organ-the brain. It is important for solving this problem to find out the real situation of the distribution of energy flux density (EFD) of EMF exposure near the front panel of the apparatus.The aim of the study is to determine and compare EMF exposure from smartphones and classic mobile phones on human head.Material and methods. The original method patented in the Russian Federation was used in this study. The used original measuring setup is also patented, developed and assembled by the authors of the study. The object of the study was classical mobile phones and smartphones widespread at the time of work.Results. We got the graphic of matrices of distribution of energy flux density (EFD) of EMF exposure in the plane against the front panel of 10 apparatus corresponding to the topography of a human head. The study revealed peculiarities of this distribution in smartphones and the classic mobile phones and got the values of energy flux density (EFD) of EMF exposure in the investigated devices acting primarily on the brain.Conclusions. The design of smartphones and mobile phones determines the overall picture of distribution of EFD of EMF exposure in the plane against the front panel for devices of a particular type. This picture must be taken into account when planning epidemiological and experimental studies to obtain comparable results. Progress in the development of mobile communication technologies has led to an increase in the electromagnetic load on users of modern devices.

This paper presents a scientific literature information extraction architecture using text mining techniques to assess the human health risk of electromagnetic fields (EMFs) generated by wireless sensor devices in Internet of Things (IoT). The proposed architecture uses three text mining techniques to extract three types of information--purpose statement, research category, and source of EMF exposure--from the scientific literature to help researchers assess the human health risk of EMFs. For the purpose statement, a representative sentence expressing the authors' intentions and purposes was extracted from the abstract text of the articles through processes of candidate sentence selection, topic lexicon creation, and weighting. For the research category, the articles were classified into three study types--epidemiological, animal experimental, and cell experimental--using a weighting process based on the predefined feature lexicon of each category. Finally, all words representing frequency bands included in the abstract text of the articles were extracted to identify the source of EMF exposure. The aforementioned text mining techniques were used to extract the information from 100 scientific articles and the performance of this architecture was proved through expert verification. The experimental results show that the proposed architecture can extract the desired information to assess the human health risk of EMFs from the scientific literature with high accuracy. [ABSTRACT FROM AUTHOR]

In this paper, a model for time-averaged realistic maximum power levels for the assessment of radio frequency (RF) electromagnetic field (EMF) exposure for the fifth generation (5G) radio base stations (RBS) employing massive MIMO is presented. The model is based on a statistical approach and developed to provide a realistic conservative RF exposure assessment for a significant proportion of all possible downlink exposure scenarios (95th percentile) in-line with requirements in a recently developed International Electrotechnical Commission standard for RF EMF exposure assessments of RBS. Factors, such as RBS utilization, time-division duplex, scheduling time, and spatial distribution of users within a cell are considered. The model is presented in terms of a closed-form equation. For an example scenario corresponding to an expected 5G RBS product, the largest realistic maximum power level was found to be less than 15% of the corresponding theoretical maximum. For far-field exposure scenarios, this corresponds to a reduction in RF EMF limit compliance distance with a factor of about 2.6. Results are given for antenna arrays of different sizes and for scenarios with beamforming in both azimuth and elevation.

In this work, monitoring of the transmit power for several base stations operating in a live 5G network (Telstra, Australia) was conducted with the purpose of analyzing the radio frequency (RF) electromagnetic field (EMF) exposure levels. The base stations made use of state-of-the-art massive MIMO antennas utilizing beamforming in order to optimize the signal strength at the user’s device. In order to characterize the actual EMF exposure from 5G base stations, knowledge of the amount of power dynamically allocated to each beam is therefore of importance. Experimental data on the spatial distribution of the base stations’ transmit power were gathered directly from the network by extracting information on the radio and baseband operations. Out of more than 13 million samples collected over 24 h, the maximum time-averaged power per beam direction was found to be well-below the theoretical maximum and lower than what was predicted by the existing statistical models. The results show that assuming constant peak power transmission in a fixed beam direction leads to an unrealistic EMF exposure assessment. This work provides insights relevant for the standardization of EMF compliance assessment methodologies applicable for 5G base stations.

Electromagnetic fields (EMFs) can affect living cells due to biochemical changes, followed by changes in levels of trace elements in serum and different organs. This study focuses on the effect of whole body exposure to EMF, presented everywhere in our environment, and on the levels of trace elements in serum, femur, brain, kidney, and liver tissues. The analyses performed on 29 guinea pigs were divided into five groups. Guinea pigs were exposed to a magnetic field of 50 Hz of 1.5 mT. Groups A and B were exposed to the magnetic field for a period of 4 h/day continuously (4 h/day) for 4 and 7 days, respectively. Groups C and D were exposed to the magnetic field for a period of 4 h/day intermittently for 4 and 7 days, respectively. Group E animals were enrolled as control. Copper (Cu), zinc (Zn), calcium (Ca), and magnesium (Mg) levels were determined by atomic absorption spectroscopy in serum, femur, brain, kidney, and liver tissues in all guinea pigs. When compared to the control groups, the changes in the levels of Cu in serum samples, femur, and kidney tissues of the treated groups were statistically significant. The same was also true for the levels of Mg in the brain, kidney, and lung tissues. Our results suggest that in vivo continuous and intermittent exposure to EMF may cause disturbances in homeostasis of bioelements. These effects could be important risk factors for toxic effects of EMF, especially in relation to deterioration of bioelements. [ABSTRACT FROM AUTHOR]