This exposure-assessment study proposes and validates a method to measure instantaneous RF exposure under typical base station load by generating defined data rates (low/medium/high) using iPerf and measuring channel power across services. Validation at four base stations suggests the approach is reliable across different times of day and loads, with reproducible results when averaging over 30 sweeps. Comparisons indicate iPerf-provoked constant data rates generally match exposure during real application usage, with few deviations beyond stated uncertainty.

This exposure/compliance assessment study collected 5- and 30-minute transmitted power data over one month from more than 400 5G FR2 beamforming base stations in urban Japan to evaluate the IEC 62232:2025 “actual maximum approach.” All measured transmitted powers were below configured maxima, with 30-minute averaged normalized maxima reported as < -8 dB, while 5-minute averaged maxima reached about -3 dB under low UE counts. The authors report that the actual maximum approach can avoid overestimation for longer averaging times, but may underestimate exposure for stations with three or fewer UEs if power is not monitored and controlled.

This exposure-assessment study proposes a Voronoi-diagram approach to visualize RF-EMF exposure across a city using personal exposimeter measurements of RMS electric field at seed points. Most mapped areas corresponded to about 1.9 V/m, with a maximum reported value of 11.4 V/m, all below the cited ICNIRP guideline level. The authors conclude the method is useful for communicating spatial variability, while also noting broader literature discussing potential health risks from EMF exposure.

This engineering/monitoring paper describes enhancements to the Serbian EMF RATEL system, which has continuously monitored RF-EMF since 2017, by adding drive test functionality to improve spatial coverage. The authors report preliminary quantitative drive test measurements and validation of the upgraded approach. The work emphasizes that characterizing spatial and temporal RF-EMF patterns can support exposure assessment relevant to public health risk evaluation.

This paper presents a traceable experimental dosimetry method to measure absorbed power density (APD) from body-mounted wireless devices at frequencies above 10 GHz. It combines a miniaturized broadband probe, a composite skin-equivalent phantom, and reconstruction/calibration procedures, with validation using reference antennas. The approach is reported as validated for 24–30 GHz and extendable to 10–45 GHz, supporting regulatory-type testing aligned with international safety standards.

This paper presents a machine-learning method to estimate ground-level electromagnetic radiation (electric field strength) in the near field of 5G base stations, using multiple technical and environmental input parameters. The authors report experimental performance with a mean absolute percentage error of about 5.89% and suggest the approach can reduce costs compared with on-site measurements. The work is positioned as supporting exposure management and base-station placement, while noting the need for careful EMF management due to potential health-risk links.

This paper applies a model-based clustering approach (Log-Normal Mixture Model) to continuous RF-EMF monitoring data from the Serbian EMF RATEL network in Novi Sad to characterize temporal exposure patterns. The analysis reports separation of night versus day exposure values and identification of daytime periods where exposure persists longer. The work is positioned as supporting improved understanding of when and where elevated exposures occur in urban environments.

This conference paper examines extrapolation factors used for in-situ EMF exposure assessment of 5G base stations in realistic indoor and outdoor scenarios. Using both frequency-selective and code-selective measurement approaches under varying traffic conditions, it reports substantial variability in extrapolated exposure estimates driven largely by antenna radiation patterns. Outdoor environments showed more stable extrapolation than indoor environments, highlighting challenges for reliable exposure assessment when antenna patterns and network configurations are not well characterized.

This paper proposes a time-averaging approach for analyzing long-term EMF exposure using time-series data from three sensors in a regulatory monitoring network. Sensors were installed at two kindergartens and one elementary school, and analyses reported daily/weekly patterns, differences between weekdays and weekends, and site-specific annual increases/decreases. The work emphasizes the value of continuous monitoring in sensitive areas, while not directly assessing health outcomes.

This engineering/methods study proposes an evolutionary computation approach (PCRO-SL) to optimize the selection of measurement points for constructing RF-EMF exposure maps. Tested on real measurements in Meco (Madrid, Spain), it reports good agreement with a reference exposure map while reducing required sampling density. The authors provide practical point-selection rules (e.g., line-of-sight within 250 m and directional sampling within 500 m) intended to maintain representativeness and avoid interpolation artifacts.