Distributed Power Allocation with Rate Constraints in Gaussian Parallel Interference Channels

This paper considers the minimization of transmit power in Gaussian parallel interference channels, subject to a rate constraint for each user. To derive decentralized solutions that do not require any cooperation among the users, we formulate this power control problem as a (generalized) Nash equilibrium game. We obtain sufficient conditions that guarantee the existence and nonemptiness of the solution set to our problem. Then, to compute the solutions of the game, we propose two distributed algorithms based on the single user waterfilling solution: The \emph{sequential} and the \emph{simultaneous} iterative waterfilling algorithms, wherein the users update their own strategies sequentially and simultaneously, respectively. We derive a unified set of sufficient conditions that guarantee the uniqueness of the solution and global convergence of both algorithms. Our results are applicable to all practical distributed multipoint-to-multipoint interference systems, either wired or wireless, where a quality of service in terms of information rate must be guaranteed for each link.Comment: Paper submitted to IEEE Transactions on Information Theory, February 17, 2007. Revised January 11, 200

Long-Run Equilibrium Modeling of Alternative Emissions Allowance Allocation Systems in Electric Power Markets

A question in the design of carbon dioxide trading systems is how allowances are to be initially allocated: by auction, by giving away fixed amounts, or by allocating based on output, fuel, or other decisions. The latter system can bias investment, operations, and pricing decisions, and increase costs relative to other systems. A nonlinear complementarity model is used to investigate long-run equilibria that would result under alternative systems for power markets characterized by time varying demand and multiple generation technologies. Existence of equilibria is shown under mild conditions. Solutions show that allocating allowances to new capacity based on fuel use or generator type can distort generation mixes, invert the operating order of power plants, and inflate consumer costs. The distortions can be smaller for tighter CO2 restrictions, and are somewhat mitigated if there are also electricity capacity markets or minimum-run restrictions on coal plants

Real and Complex Monotone Communication Games

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 that optimize a given performance criterion, at the cost of limited signaling among the players. This is a major departure from existing best-response algorithms, whose convergence conditions imply the uniqueness of the NE. Some of our results hinge on the use of VI problems directly in the complex domain; the study of these new kind of VIs also represents a noteworthy innovative contribution. We then apply the developed methods to solve some new generalizations of SISO and MIMO games in cognitive radios and femtocell systems, showing a considerable performance improvement over classical pure noncooperative schemes.Comment: to appear on IEEE Transactions in Information Theor