Real and complex analysis, 3rd ed.
Real and complex analysis, 3rd ed.
Parallel and distributed computation: numerical methods
Parallel and distributed computation: numerical methods
Elements of information theory
Elements of information theory
On the Mean Value Theorem, inequality, and inclusion
American Mathematical Monthly
Understanding digital subscriber line technology
Understanding digital subscriber line technology
Analysis of iterative waterfilling algorithm for multiuser power control in digital subscriber lines
EURASIP Journal on Applied Signal Processing
Autonomous Spectrum Balancing for Digital Subscriber Lines
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Optimized signaling for MIMO interference systems with feedback
IEEE Transactions on Signal Processing
Complex-Valued Matrix Differentiation: Techniques and Key Results
IEEE Transactions on Signal Processing
Design challenges for energy-constrained ad hoc wireless networks
IEEE Wireless Communications
Power Management in MIMO Ad Hoc Networks: A Game-Theoretic Approach
IEEE Transactions on Wireless Communications
IEEE Transactions on Wireless Communications
Asynchronous Iterative Water-Filling for Gaussian Frequency-Selective Interference Channels
IEEE Transactions on Information Theory
A survey on wireless mesh networks
IEEE Communications Magazine
Distributed multiuser power control for digital subscriber lines
IEEE Journal on Selected Areas in Communications
Spectrum sharing for unlicensed bands
IEEE Journal on Selected Areas in Communications
Convergence of Iterative Waterfilling Algorithm for Gaussian Interference Channels
IEEE Journal on Selected Areas in Communications
Competition Versus Cooperation on the MISO Interference Channel
IEEE Journal on Selected Areas in Communications
Competitive Design of Multiuser MIMO Systems Based on Game Theory: A Unified View
IEEE Journal on Selected Areas in Communications
Transmission strategies in MIMO ad hoc networks
EURASIP Journal on Wireless Communications and Networking - Special issue on optimization techniques in wireless communications
Competitive optimization of cognitive radio MIMO systems via game theory
GameNets'09 Proceedings of the First ICST international conference on Game Theory for Networks
MIMO cognitive radio: a game theoretical approach
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Distributed stochastic approximation for constrained and unconstrained optimization
Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools
Dynamic power allocation games in parallel multiple access channels
Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools
Learning to use the spectrum in self-configuring heterogenous networks: a logit equilibrium approach
Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools
Welfare-maximizing correlated equilibria using Kantorovich polynomials with sparsity
Journal of Global Optimization
Hi-index | 35.69 |
This paper considers the noncooperative maximization of mutual information in the vector Gaussian interference channel in a flilly distributed fashion via game theory. This problem has been widely studied in a number of works during the past decade for frequency-selective channels, and recently for the more general multiple-input multiple-output (MIMO) case, for which the state-of-the art results are valid only for nonsingular square channel matrices. Surprisingly, these results do not hold true when the channel matrices are rectangular and/or rank deficient matrices. The goal of this paper is to provide a complete characterization of the MIMO game for arbitrary channel matrices, in terms of conditions guaranteeing both the uniqueness of the Nash equilibrium and the convergence of asynchronous distributed iterative waterfilling algorithms. Our analysis hinges on new technical intermediate results, such as a new expression for the MIMO waterfilling projection valid (also) for singular matrices, a mean-value theorem for complex matrix-valued functions, and a general contraction theorem for the multiuser MIMO watefilling mapping valid for arbitrary channel matrices. The quite surprising result is that uniqueness/convergence conditions in the case of tall (possibly singular) channel matrices are more restrictive than those required in the case of (full rank) fat channel matrices. We also propose a modified game and algorithm with milder conditions for the uniqueness of the equilibrium and convergence, and virtually the same performance (in terms of Nash equilibria) of the original game.