Power Allocation Games on Interference Channels with Complete and Partial Information

TL;DR

This paper studies power allocation strategies in interference channels with varying levels of channel state information, formulating the problem as a variational inequality to find Nash equilibria.

Contribution

It introduces a unified VI-based framework for power allocation under complete, partial, and minimal channel knowledge scenarios.

Findings

Nash equilibria can be characterized as solutions to a variational inequality.

Algorithms are proposed to compute equilibria efficiently.

Framework applies to different information assumptions in interference channels.

Abstract

We consider a wireless channel shared by multiple transmitter-receiver pairs. Their transmissions interfere with each other. Each transmitter-receiver pair aims to maximize its long-term average transmission rate subject to an average power constraint. This scenario is modeled as a stochastic game under different assumptions. We first assume that each transmitter and receiver has knowledge of all direct and cross link channel gains. We later relax the assumption to the knowledge of incident channel gains and then further relax to the knowledge of the direct link channel gains only. In all the cases, we formulate the problem of finding the Nash equilibrium as a variational inequality (VI) problem and present an algorithm to solve the VI.