User Association for Offloading in Heterogeneous Network Based on Matern Cluster Process

TL;DR

This paper models user association in heterogeneous networks using a Matern cluster process for small base stations, deriving probabilities and rates, and highlighting the impact of base station density and cluster radius on offloading efficiency.

Contribution

It introduces a realistic model with inter-tier dependence and user-BS dependence, analyzing association probabilities and ergodic rates with stochastic geometry.

Findings

Clustered SBSs enable more aggressive offloading.

Density and radius jointly influence association probabilities.

Model captures realistic user and BS distributions.

Abstract

Future mobile networks are converging toward heterogeneous multi-tier networks, where various classes of base stations (BS) are deployed based on user demand. So it is quite necessary to utilize the BSs resources rationally when BSs are sufficient. In this paper, we develop a more realistic model that fully considering the inter-tier dependence and the dependence between users and BSs, where the macro base stations (MBSs) are distributed according to a homogeneous Poisson point process (PPP) and the small base stations (SBSs) follows a Matern cluster process (MCP) whose parent points are located in the positions of the MBSs in order to offload the users from the over-loaded MBSs. We also assume the users are just randomly located in the circles centered at the MBSs. Under this model, we derive the association probability and the average ergodic rate by stochastic geometry. An interesting result that the density of MBS and the radius of the clusters jointly affect the association probabilities in a joint form is obtained. We also observe that using the clustered SBSs results in aggressive offloading compared with previous cellular networks.