Role of Different Spatial Point Processes on Network Densification towards 5G Development: Coverage and Rate Analysis

Abstract

The rapid growth in tele traffic density has enforced the modern wireless network to evolve in the direction of network densification which is speculated to play a key role in designing deployment strategies for 5G wireless communication standards. Modeling the dense small cell network by Spatial Point Process (SPP) provides an efficient and tractable technique to investigate the network performance using the stochastic geometry theory, in terms of coverage probability (CP) and average rate (AR). This paper aims to provide a reasonable performance analysis of three established SPPs, namely, Binomial Point process (BPP), Homogeneous Poisson Point Process (HPPP), Non-Homogeneous Poisson Point Process (NHPPP) in terms of achieved coverage and rate. Furthermore, the Close-In (CI) reference path-loss model plays a pivotal role in estimating downlink SINR which in turn leads to derive the expressions for CP and AR. It is observed that with the increase in tele-density as well as eNB density the NHPPP outperforms both BPP and HPPP in providing better coverage and rate.