Analysis of heterogeneous cellular networks interference with biased cell association using Poisson cluster processes

Abstract

Heterogeneous cellular networks (HetNets) achieve high data rates and coverage gains by distributing small cells over macro-cells based on random user demand. Recently, a novel approach to use stochastic geometry for analyzing the communication performance over random wireless network has gained popularity. These approach treat the location of base stations (BSs) as homogeneous Poisson point process (PPP) by assuming that the nodes are uniformly distributed in space. However, due to geographical factors, it may be the case for mobile users to cluster around highly populated cities and the PPP assumption does not provide an accurate model for the interference in these conditions. This motivates us to find better ways to characterize the aggregate interference. To this end, we consider K-tier HetNets where each tier may differ in terms of transmit power, node densities, link reliabilities and the transmitting nodes are clustered following a Poisson cluster process (PCP). We evaluate the outage probability and the average achievable rate and derive tight bounds that simplify the numerical computation. The main advantage of this approach is that our results provide complete theoretical tools to model interference over an urban and rural area whether it is clustered or not.