Unveiling Passive and Active EMF Exposure in Large-Scale Cellular Networks

TL;DR

This paper introduces a stochastic geometry framework to analyze both passive and active electromagnetic field exposure in large-scale 5G cellular networks, highlighting the significance of passive exposure from nearby users at high densities.

Contribution

It models EMF exposure considering passive and active sources using PPP and Matern cluster processes, providing new insights into exposure distribution and coverage trade-offs.

Findings

Passive exposure from other users becomes significant at high user densities.

Passive radiation can surpass active exposure from the user's own device at very high densities.

The framework quantifies the trade-off between EMF exposure and network coverage.

Abstract

With the development of fifth-generation (5G) networks, the number of user equipments (UE) increases dramatically. However, the potential health risks from electromagnetic fields (EMF) tend to be a public concern. Generally, EMF exposure-related analysis mainly considers the passive exposure from base stations (BSs) and active exposure that results from the user's personal devices while communicating. However, the passive radiation that is generated by nearby devices of other users is typically ignored. In fact, with the increase in the density of UE, their passive exposure to human bodies can no longer be ignored. In this work, we propose a stochastic geometry framework to analyze the EMF exposure from active and passive radiation sources. In particular, considering a typical user, we account for their exposure to EMF from BSs, their own UE, and other UE. We derive the distribution of the Exposure index (EI) and the coverage probability for two typical models for spatial distributions of UE, i.e., \textit{i)} a Poisson point process (PPP); \textit{ii)} a Matern cluster process. Also, we show the trade-off between the EMF exposure and the coverage probability. Our numerical results suggest that the passive exposure from other users is non-negligible compared to the exposure from BSs when user density is $10^2$ times higher than BS density, and non-negligible compared to active exposure from the user's own UE when user density is $10^5$ times the BS density.