As the roll-out of the fifth generation (5G) of mobile telecommunications is well underway, standardized methods to assess the human exposure to radiofrequency electromagnetic fields from 5G base station radios are needed in addition to existing numerical models and preliminary measurement studies. Challenges following the introduction of 5G New Radio (NR) include the utilization of new spectrum bands and the widespread use of technological advances such as Massive MIMO (Multiple-Input Multiple-Output) and beamforming. We propose a comprehensive and ready-to-use exposure assessment methodology for use with common spectrum analyzer equipment to measure or calculate in-situ the time-averaged instantaneous exposure and the theoretical maximum exposure from 5G NR base stations. Besides providing the correct method and equipment settings to capture the instantaneous exposure, the procedure also comprises a number of steps that involve the identification of the Synchronization Signal Block, which is the only 5G NR component that is transmitted periodically and at constant power, the assessment of the power density carried by its resources, and the subsequent extrapolation to the theoretical maximum exposure level. The procedure was validated on site for a 5G NR base station operating at 3.5 GHz, but it should be generally applicable to any 5G NR signal, i.e., as is for any sub-6 GHz signal and after adjustment of the proposed measurement settings for signals in the millimeter-wave range.

This paper describes the assessment of radiofrequency (RF) electromagnetic field (EMF) exposure from fifth generation (5G) new radio (NR) base stations in a commercial NR network in Bern, Switzerland. During the measurement campaign, four base station sites were investigated and the exposure induced by the NR massive multiple-input-multiple-output (MaMIMO) antennas was assessed at 22 positions, at distances from the base station between 30 m and 410 m. The NR base stations operated at 3.6 GHz and used codebook-based beamforming. While the actual field levels without inducing downlink traffic were very low (<0.05 V/m) due to a low traffic load and low antenna input powers of up to 8 W, setting up a maximum downlink traffic stream towards user equipment resulted in a time-averaged exposure level of up to 0.4 V/m, whereas the maximum extrapolated exposure level reached 0.6 V/m. Extrapolated to an antenna input power of 200 W, values of 4.3 V/m and 4.9 V/m, respectively, were obtained, which amount to 0.5–0.6% of the reference level recommended by the International Commission on Non-Ionizing Radiation Protection (ICNIRP). In Bern, it was found that the impact of the NR network on the total environmental RF exposure was very limited; with maximum downlink, it contributed 2% on average. Finally, it was also concluded that extrapolation to the maximum exposure level can be done without prior knowledge of the radiation patterns, directly based on the measurement of the Physical Downlink Shared Channel (PDSCH) resource elements.

Advances in wireless sensor technologies and MEMS have made it possible to automatically monitor the health status of dairy cows using Internet of things (IoT) and wireless body area networks. Since on‐cow measuring devices are energy constrained, a proper characterisation of the off‐body wireless channel between the on‐cow sensor nodes and the back‐end base station is required for an optimised deployment of these networks in barns. In this Letter, the long range (LoRa) off‐body wireless channel has been characterised at 868 MHz, a typical IoT frequency. Both path loss and temporal fading were investigated using LoRa motes. Based on this characterisation, network planning and energy consumption optimisation of the on‐body nodes could be performed, which enables the deployment of reliable dairy cow monitoring systems.

Of particular interest within fifth generation (5G) cellular networks are the typical levels of radiofrequency (RF) electromagnetic fields (EMFs) emitted by ‘small cells’, low-power base stations, which are installed such that both workers and members of the general public can come in close proximity with them. In this study, RF-EMF measurements were performed near two 5G New Radio (NR) base stations, one with an Advanced Antenna System (AAS) capable of beamforming and the other a traditional microcell. At various positions near the base stations, with distances ranging between 0.5 m and 100 m, both the worst-case and time-averaged field levels under maximized downlink traffic load were assessed. Moreover, from these measurements, estimates were made of the typical exposures for various cases involving users and non-users. Comparison to the maximum permissible exposure limits issued by the International Commission on Non-Ionizing Radiation Protection (ICNIRP) resulted in maximum exposure ratios of 0.15 (occupational, at 0.5 m) and 0.68 (general public, at 1.3 m). The exposure of non-users was potentially much lower, depending on the activity of other users serviced by the base station and its beamforming capabilities: 5 to 30 times lower in the case of an AAS base station compared to barely lower to 30 times lower for a traditional antenna.

In an increasingly wireless world, spatiotemporal monitoring of the exposure to environmental radiofrequency (RF) electromagnetic fields (EMF) is crucial to appease public uncertainty and anxiety about RF-EMF. However, although the advent of smart city infrastructures allows for dense networks of distributed sensors, the costs of accurate RF sensors remain high, and dedicated RF monitoring networks remain rare. This paper describes a comprehensive study comprising the design of a low-cost RF-EMF sensor node capable of monitoring four frequency bands used by wireless telecommunications with an unparalleled temporal resolution, its application in a small-scale distributed sensor network consisting of both fixed (on building façades) and mobile sensor nodes (on postal vans), and the subsequent analysis of over a year of data between January 2019 and May 2020, during which slightly less than 10 million samples were collected. From the fixed nodes’ results, the potential errors were determined that are induced when sampling at lower speeds (e.g., one sample per 15 min) and measuring for shorter periods of time (e.g., a few weeks), as well as an adequate resolution (30 min) for diurnal and weekly temporal profiles which sufficiently preserves short-term variations. Furthermore, based on the correlation between the sensors, an adequate density of 100 sensor nodes per km² was deduced for future networks. Finally, the mobile sensor nodes were used to identify potential RF-EMF exposure hotspots in a previously unattainable area of more than 60 km². In summary, through the analysis of a small number of RF-EMF sensor nodes (both fixed and mobile) in an urban area, this study offers invaluable insights applicable to future designs and deployments of distributed RF-EMF sensor networks.

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.