Optimizing User Association and Activation Fractions in Heterogeneous Wireless Networks

TL;DR

This paper presents a joint optimization framework for user association and activation fractions in HetNets, improving fairness and interference management through distributed algorithms with proven convergence.

Contribution

It introduces a novel alternating optimization approach with distributed algorithms for joint user association and activation fractions in HetNets, with theoretical guarantees.

Findings

Enhanced network fairness and performance in simulations

Distributed algorithms with provable convergence

Effective interference management through optimized activation fractions

Abstract

We consider the problem of maximizing the alpha-fairness utility over the downlink of a heterogeneous wireless network (HetNet) by jointly optimizing the association of users to transmission points (TPs) and the activation fractions of all TPs. Activation fraction of each TP is the fraction of the frame duration for which it is active, and together these fractions influence the interference seen in the network. To address this joint optimization problem we adopt an approach wherein the activation fractions and the user associations are optimized in an alternating manner. The sub-problem of determining the optimal activation fractions is solved using an auxiliary function method that we show is provably convergent and is amenable to distributed implementation. On the other hand, the sub-problem of determining the user association is solved via a simple combinatorial algorithm. Meaningful performance guarantees are derived and a distributed variant offering identical guarantees is also proposed. The significant benefits of using the proposed algorithms are then demonstrated via realistic simulations.