Personal exposure to Radio-Frequency Electromagnetic Fields (RF-EMFs) was studied using personal measurements in five different microenvironments in each of five cities (Brussels, Antwerp, Ghent, Bruges and Hasselt) in Flanders, Belgium. These measurements were carried out by two researchers using on-body calibrated personal exposimeters. In three out of the five studied cities (Brussels, Ghent and Bruges), temporal aspects of personal exposure to RF-EMFs were studied as well. Measurements during and outside of rush hours (7:00-9:15 and 16:30-19:00) were compared. Likewise, measurements were executed during night time and compared to the ones measured during working hours. Representativeness and repeatability of the measurement method was studied as well. The highest mean total exposure was found in Brussels (2.63 mW/m²), the most densely populated city in this study. However, we measured higher downlink exposure in Antwerp than in Brussels, which might be an effect of the stronger legislation on base stations in Brussels. The measurements and used protocol were found to be both repeatable over time (r=0.95 for median total exposure) and representative for the studied microenvironments in terms of path selection (r=0.88 for median total exposure). Finally, in 10 out of the 13 on-body calibrated frequency bands we found that the measurement devices underestimate the intensity of the incident RF-EMFs with median underestimations up to 68%.

Background The general population is exposed to Radio-Frequency Electromagnetic Fields (RF-EMFs) used by telecommunication networks. Previous studies developed methods to assess this exposure. These methods will be inadequate to accurately assess exposure in 5G technologies or other wireless technologies using adaptive antennas. This is due to the fact that 5G NR (new radio) base stations will focus actively on connected users, resulting in a high spatio-temporal variations in the RF-EMFs. This increases the measurement uncertainty in personal measurements of RF-EMF exposure. Furthermore, a user’s exposure from base stations will be dependent on the amount of data usage, adding a new component to the auto-induced exposure, which is often omitted in current studies. Goals The objective of this paper is to develop a general study protocol for future personal RF-EMF exposure research adapted to 5G technologies. This protocol will include the assessment of auto-induced exposure of both a user’s own devices and the networks’ base stations. Method This study draws from lessons learned from previous RF-EMF exposure research and current knowledge on 5G technologies, including studies simulating 5G NR base stations and measurements around 5G NR test sites. Results To account for auto-induced exposure, an activity-based approach is introduced. In survey studies, an RF-EMF sensor is fixed on the participants’ mobile device(s). Based on the measured power density, GPS data and movement and proximity sensors, different activities can be clustered and the exposure during each activity is evaluated. In microenvironmental measurements, a trained researcher performs measurements in predefined microenvironments with a mobile device equipped with the RF-EMF sensor. The mobile device is programmed to repeat a sequence of data transmission scenarios (different amounts of uplink and downlink data transmissions). Based on simulations, the amount of exposure induced in the body when the user device is at a certain location relative to the body, can be evaluated. Conclusion Our protocol addresses the main challenges to personal exposure measurement introduced by 5G NR. A systematic method to evaluate a user’s auto-induced exposure is introduced.

Background The general population is exposed to Radio-Frequency Electromagnetic Fields (RF-EMFs) used by telecommunication networks. Previous studies developed methods to assess this exposure. These methods will be inadequate to accurately assess exposure in 5G technologies. This is due to the fact that 5G NR (new radio) base stations will focus actively on connected users, resulting in a high spatio-temporal variations in the RF-EMFs. This increases the measurement uncertainty in personal measurements of RF-EMF exposure. Furthermore, a user’s exposure from base stations will be dependent on the amount of data usage, adding a new component to the auto-induced exposure, which is often omitted in current studies. Methods The objective of this paper is to develop a general study protocol for future personal RF-EMF exposure research adapted to 5G technologies. This protocol will include the assessment of auto-induced exposure of both a user’s own devices and the networks’ base stations. Results To account for auto-induced exposure, an activity-based approach is introduced. In survey studies, an RF-EMF sensor is fixed on the participants’ mobile device(s). Based on the measured power density, GPS data and movement and proximity sensors, different activities can be clustered and the exposure during each activity is evaluated. In microenvironmental measurements, a trained researcher performs measurements in predefined microenvironments with a mobile device equipped with the RF-EMF sensor. The mobile device is programmed to repeat a sequence of data transmission scenarios (different amounts of uplink and downlink data transmissions). Based on simulations, the amount of exposure induced in the body when the user device is at a certain location relative to the body, can be evaluated. Conclusion Our protocol addresses the main challenges to personal exposure measurement introduced by 5G NR. A systematic method to evaluate a user’s auto-induced exposure is introduced.

The goal of this paper is to experimentally assess the field enhancement and hotspot size of radio frequency electromagnetic fields created by the Maximum Ratio Combining (MRC) precoding scheme using lab measurements at 3.5, 5.5 and 11 GHz. MRC is an adaptive precoding scheme used by Massive Multiple Input Multiple Output systems, one of the enabling techniques of the fifth generation of telecommunications (5G). A virtual antenna array was used to compare MRC with two passive precoding schemes: the Random Phase Model (RPM) and the Centerline Beam Model (CBM). The field enhancement going from CBM to MRC was largest in obstructed line of sight (OLOS), ranging from 1.9 to 7.4 dB. The field enhancement going from RPM to MRC was about 9.5 dB across frequency bands in both line of sight (LOS) and OLOS. The hotspot size, quantified by the full width at half maximum (FWHM), ranged from 0.5 wavelengths to one wavelength.

The width of a beam produced by MaMIMO arrays will affect a user's exposure to RF-EMFs. We performed measurements in an anechoic chamber using a virtual arrays and successfully assessed this beamwidth. We validated our measurements with simulations.