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Published March 2010 | Published
Book Section - Chapter Open

Robust rate-maximization game under bounded channel uncertainty

Abstract

The problem of decentralized power allocation for competitive rate maximization in a frequency-selective Gaussian interference channel is considered. In the absence of perfect knowledge of channel state information (CSI), a distribution-free robust game is formulated. A robust-optimization equilibrium (RE) is proposed where each player formulates a best response to the worst-case interference. The conditions for existence, uniqueness and convergence of the RE are derived. It is shown that the convergence reduces as the uncertainty increases. Simulations show an interesting phenomenon where the proposed RE moves closer to a Pareto-optimal solution as the CSI uncertainty bound increases, when compared to the classical Nash equilibrium under perfect CSI. Thus, the robust-optimization equilibrium successfully counters bounded channel uncertainty and increases system sum-rate due to users being more conservative about causing interference to other users.

Additional Information

© 2010 IEEE. This work is supported by EPSRC grant EP/F065477/1. The second author is supported in part by ARO Grant W911NF-06-1-0076. We thank Dr. Ishai Menache, MIT for his input on robust game theory and Dr. Gesualdo Scutari, Hong Kong University of Science and Technology for initial guidance and advice on waterfilling algorithms.

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