Interference Avoidance Methods for Wireless Systems (Information Technology Transmission, Processing and Storage)
Analysis and design of cognitive radio networks and distributed radio resource management algorithms
Analysis and design of cognitive radio networks and distributed radio resource management algorithms
A game-theoretic framework for interference avoidance
IEEE Transactions on Communications
Using game theory to analyze wireless ad hoc networks
IEEE Communications Surveys & Tutorials
Wireless systems and interference avoidance
IEEE Transactions on Wireless Communications
Simultaneous Water Filling in Mutually Interfering Systems
IEEE Transactions on Wireless Communications
Iterative construction of optimum signature sequence sets in synchronous CDMA systems
IEEE Transactions on Information Theory
CDMA codeword optimization: interference avoidance and convergence via class warfare
IEEE Transactions on Information Theory
On the stability of distributed sequence adaptation for cellular asynchronous DS-CDMA systems
IEEE Transactions on Information Theory
Power control and spreading sequence allocation in a CDMA forward link
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Sum capacity and TSC bounds in collaborative multibase wireless systems
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Spectrum sharing for unlicensed bands
IEEE Journal on Selected Areas in Communications
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Direct extensions of distributed greedy interference avoidance (IA) techniques developed for centralized networks to networks with multiple distributed receivers (as in ad hoc networks) are not guaranteed to converge. Motivated by this fact, we develop a waveform adaptation (WA) algorithm framework for IA based on potential game theory. The potential game model ensures the convergence of the designed algorithms in distributed networks and leads to desirable network solutions. Properties of the game model are then exploited to design distributed implementations of the algorithm that involve limited feedback in the network. Finally, variations of IA algorithms including IA with respect to legacy systems and IA with combined transmit-power and WA adaptations are investigated.