Large Player games on Wireless Networks

TL;DR

This paper models a wireless network with multiple users as a Markov game, demonstrating equilibrium existence, invariance of policies above a user threshold, and providing a decentralized method for policy computation.

Contribution

It introduces a novel Markov game framework for multi-user wireless networks, proving equilibrium properties and offering a decentralized algorithm for policy determination.

Findings

All users achieve the same throughput above a certain user threshold.

Equilibrium policies are invariant when the number of users exceeds this threshold.

Users can compute policies independently using linear programs without inter-user information.

Abstract

We consider a scenario where $N$ users send packets to a common access point. The receiver decodes the message of each user by treating the other user's signals as noise. Associated with each user is its channel state and a finite queue which varies with time. Each user allocates his power and the admission control variable dynamically to maximize his expected throughput. Each user is unaware of the states, and actions taken, by the other users. This problem is formulated as a Markov game for which we show the existence of equilibrium and an algorithm to compute the equilibrium policies. We then show that when the number of users exceeds a particular threshold, the throughput of all users at all the equilibria are the same. Furthermore the equilibrium policies of the users are invariant as long as the number of users remain above the latter threshold. We also show that each user can compute these policies using a sequence of linear programs which does not depend upon the parameters of the other users. Hence, these policies can be computed by each user without any information or feedback from the other users. We then provide numerical results which verify our theoretical results.