🤖 AI Summary
This study addresses the sustainable deployment of 5G networks by evaluating and mitigating electromagnetic field (EMF) exposure while maintaining performance. Leveraging a stochastic geometry framework, it models base station spatial distributions using both Poisson point processes (PPP) and the more realistic beta-Ginibre point process (beta-GPP), within an EN-DC multi-connectivity scenario. The analysis combines theoretical derivations, Monte Carlo simulations, and empirical validation using real-world measurements from Paris. The work introduces a novel metric—Radiation Energy per Bit in the Downlink (REBT-DL)—and, for the first time, incorporates beta-GPP into EMF exposure modeling. Results reveal that network configuration significantly influences both EMF exposure and energy efficiency, offering a practical assessment tool to support the design of environmentally sustainable 5G networks.
📝 Abstract
This paper builds stochastic geometry frameworks for analyzing downlink electromagnetic field (EMF) exposure and efficiency in 5G multi-connectivity networks, using 5G E-UTRAN New Radio - Dual Connectivity (EN-DC) configuration as a representative use case. The Poisson point process (PPP) and the beta-Ginibre point process (beta-GPP) are used to model the spatial distribution of base stations (BSs), where beta-GPP effectively captures the repulsion observed in real deployments. We derive tractable expressions for the distribution of EMF exposure and validate the framework through both Monte Carlo simulations and real BS data from Paris. In addition to conventional metrics, we introduce the Radiated Energy per Bit Transmitted in the Downlink (REBT-DL), which accounts for throughput and received power. Results show that network configuration significantly affect exposure and REBTDL, highlighting the relevance of energy-aware deployment strategies and confirming the proposed approach as a comprehensive tool for sustainable network evaluation. The results also confirm that \b{eta}-GPP provides a more accurate fit to practical deployments than PPP.