# Electromagnetic Field-Aware Radio Resource Management for 5G and Beyond: A Survey
## 4 EMF Exposure Level and 5G Technologies
### EMF Exposure and 5G Radio Access Technologies
Thus, the authors proposed a comprehensive and ready-to-use exposure assessment methodology to measure or calculate in situ the time-averaged instantaneous exposure and theoretical maximum exposure from 5G NR BSs using a common spectrum analyzer. The proposed measurements consisted of six steps. Firstly, the frequency range at the measurement location and the actual position of the synchronization signal (SS) burst were determined. Next, the electric field strength per resource element (RE) of the dominant synchronization signal block (SSB) was measured. Then, the EMF exposure was evaluated based on the instantaneous electric field strength. The authors then extrapolated the electric field strength per RE of the dominant SSB beam (\(E_{RE,SSB}\)) compared to the theoretical maximum exposure level (\(E_{\mathrm{max}}\)) and compared the exposure levels with the relevant exposure limits introduced by the ICNIRP [10]. Finally, the proposed methodology was validated by an on-site experiment carried out for a 5G NR BS operating at 3.5 GHz in Dusseldorf, Germany. Based on the findings, the worst-case downlink exposure level was about 130 to 170 times higher when the 5G NR channel was fully occupied with downlink resources compared to the scenarios with a single UE. However, in all testing scenarios, the electric field strength values were less than the reference limits (61 V/m) specified by the ICNIRP/IEEE [10]. It was concluded that EMF exposure tests for 5G NR signals at higher frequencies, such as mmWave signals, could not be performed using the proposed method. However, the experimental procedure carried out for a 3.5 GHz BS remains valid for the mmWave band. In [50], the authors compare different in situ methodologies for assessing RF EMF exposure from 5G base stations operating in the FR2 frequency range. The study evaluates the accuracy, precision, and feasibility of various measurement techniques, highlighting the challenges associated with RF EMF exposure assessment in complex urban environments. Similarly, [51] investigates the relationship between extrapolated field strengths, distance, measurement time, and induced traffic from 5G C-band base stations, emphasizing the need for accurate extrapolation methods in densely populated areas. The study in [52] provides a comprehensive analysis of RF EMF exposure in diverse micro-environments across rural and urban regions in France, noting significant variations due to environmental factors and base station configurations. In [53], measurements of EMF exposure and throughput performance for a 3.5 GHz standalone 5G fixed wireless access (FWA) deployment in a baseball stadium reveal high throughput with controlled EMF exposure levels. The findings in [54] underscore the dominant role of smartphones in 5G-related RF exposure, attributing increased exposure to user behavior and device characteristics, and call for targeted mitigation strategies. The work in [55]compares EMF exposure and network throughput before and after 5G activation in a residential area, showing significant throughput gains with exposure remaining within safe limits. The authors of [56] present measurements of EMF exposure from mobile network antennas in Luxembourg. The paper details the methodologies used to assess exposure levels in various locations around the country, concluding that EMF exposure from mobile antennas is generally within recommended limits, though further monitoring is needed for high-density areas. Similarly, [57] evaluates the effective isotropic radiated power (EIRP) of 5G base stations during large stadium events, demonstrating that careful planning is crucial for ensuring EMF safety. The authors of [58] investigate the use of physics-informed machine learning models to predict RF-EMF exposure in massive MIMO systems. By combining physical models with machine learning algorithms, they improve exposure predictions and show that this approach can accurately model complex scenarios involving massive MIMO technology and RF-EMF exposure.