The Influence of Gaussian Signaling Approximation on Error Performance in Cellular Networks

Abstract

Stochastic geometry analysis for cellular networks is mostly limited to outage probability and ergodic rate, which abstract many important wireless communication aspects. Recently, a novel technique based on the Equivalent-in-Distribution (EiD) approach is proposed to extend the analysis to capture these metrics and analyze bit error probability (BEP) and symbol error probability (SEP). However, the EiD approach considerably increases the complexity of the analysis. In this letter, we propose an approximate yet accurate framework, that is also able to capture fine wireless communication details similar to the EiD approach, but with simpler analysis. The proposed methodology is verified against the exact EiD analysis in both downlink and uplink cellular networks scenarios.