SIR Meta Distribution of K-Tier Downlink Heterogeneous Cellular Networks with Cell Range Expansion

TL;DR

This paper analyzes the SIR meta distribution in K-tier heterogeneous cellular networks with cell range expansion, providing exact expressions and approximations for key performance metrics to improve network understanding.

Contribution

It introduces a refined SIR meta distribution framework for K-tier HCNs with range expansion, deriving new expressions for moments and performance bounds.

Findings

Biases reduce overall mean success probability.

Meta distribution approximations are highly accurate.

Lower bounds for active probabilities ensure finite local delay.

Abstract

Heterogeneous cellular networks (HCNs) constitute a necessary step in the evolution of cellular networks. In this paper, we apply the signal-to-interference ratio (SIR) meta distribution framework for a refined SIR performance analysis of HCNs, focusing on K-tier heterogeneous cellular networks based on the homogeneous independent Poisson point process (HIP) model, with range expansion bias (offloading bias) in each tier. Expressions for the b-th moment of the conditional success probability for both the entire network and each tier are derived, based on which the exact meta distributions and the beta approximations are evaluated and compared. Key performance metrics including the mean success probability, the variance of the conditional success probability, the mean local delay and the asymptotic SIR gains of each tier are obtained. The results show that the biases are detrimental to the overall mean success probability of the whole network and that the b-th moment curve (versus the SIR threshold) of the conditional success probability of each tier can be excellently approximated by the horizontal shifted versions of the first moment curve of the single-tier PPP network. We also provide lower bounds for the region of the active probabilities of the base stations to keep the mean local delay of each tier finite.