Distributed Linear Precoder Optimization and Base Station Selection for an Uplink Heterogeneous Network

TL;DR

This paper proposes a distributed game-theoretic approach for joint linear precoder optimization and base station selection in uplink heterogeneous networks, effectively balancing load and maximizing throughput.

Contribution

It introduces a novel noncooperative game formulation with utility functions ensuring Nash equilibria align with local optima of the sum utility.

Findings

Distributed algorithm achieves high throughput

Effectively relieves base station congestion

Ensures load balancing in heterogeneous networks

Abstract

In a heterogeneous wireless cellular network, each user may be covered by multiple access points such as macro/pico/relay/femto base stations (BS). An effective approach to maximize the sum utility (e.g., system throughput) in such a network is to jointly optimize users' linear procoders as well as their base station associations. In this paper we first show that this joint optimization problem is NP-hard and thus is difficult to solve to global optimality. To find a locally optimal solution, we formulate the problem as a noncooperative game in which the users and the BSs both act as players. We introduce a set of new utility functions for the players and show that every Nash equilibrium (NE) of the resulting game is a stationary solution of the original sum utility maximization problem. Moreover, we develop a best-response type algorithm that allows the players to distributedly reach a NE of the game. Simulation results show that the proposed distributed algorithm can effectively relieve local BS congestion and simultaneously achieve high throughput and load balancing in a heterogeneous network.