Real and Complex Monotone Communication Games
Gesualdo Scutari, Francisco Facchinei, Jong-Shi Pang, and Daniel P., Palomar

TL;DR
This paper introduces a new class of distributed algorithms for convex Nash Equilibrium Problems in complex and matrix variables, enabling equilibrium selection based on performance criteria in communication games.
Contribution
It develops asynchronous best-response algorithms for general convex NEPs with complex variables, using Variational Inequality techniques for convergence and equilibrium selection.
Findings
Algorithms effectively solve complex matrix NEPs.
Convergence achieved even with multiple equilibria.
Performance improvements in cognitive radio and femtocell systems.
Abstract
Noncooperative game-theoretic tools have been increasingly used to study many important resource allocation problems in communications, networking, smart grids, and portfolio optimization. In this paper, we consider a general class of convex Nash Equilibrium Problems (NEPs), where each player aims to solve an arbitrary smooth convex optimization problem. Differently from most of current works, we do not assume any specific structure for the players' problems, and we allow the optimization variables of the players to be matrices in the complex domain. Our main contribution is the design of a novel class of distributed (asynchronous) best-response- algorithms suitable for solving the proposed NEPs, even in the presence of multiple solutions. The new methods, whose convergence analysis is based on Variational Inequality (VI) techniques, can select, among all the equilibria of a game, those…
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