Large Player games on Wireless Networks
For wireless network designers, this work provides theoretical guarantees and a practical decentralized algorithm for throughput maximization in large-scale multi-user systems.
The paper studies a wireless network with N users sending packets to a common access point, where each user dynamically allocates power and admission control to maximize expected throughput without knowledge of other users' states or actions. The authors prove the existence of equilibrium, show that beyond a user threshold all equilibria yield the same throughput and invariant policies, and provide a decentralized algorithm using linear programs that requires no information from other users.
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.