UBC Theses and Dissertations
Game theoretic methods for networked sensors and dynamic spectrum access Maskery, Michael
Automated devices enabled by wireless communications are deployed for a variety of purposes. As they become more ubiquitous, their interaction becomes increasingly important for coexistence when sharing a scarce resource, and for leveraging potential cooperation to achieve larger design goals. This thesis investigates the use of game theory as a tool for design and analysis of networked systems of automated devices in the areas of naval defence, wireless environmental monitoring through sensor networks, and cognitive radio wireless communications. In the first part, decentralized operation of naval platforms deploying electronic countermeasures against missile threats is studied. The problem is formulated as a stochastic game in which platforms independently plan and execute dynamic strategies to defeat threats in two situations: where coordination is impossible due to lack of communications, and where platforms hold different objectives but can coordinate, according to the military doctrine of Network Enabled Operations. The result is a flexible, robust model for missile deflection for advanced naval groups. Next, the problem of cooperative environmental monitoring and communication in energy-constrained wireless sensor networks is considered from a game-theoretic perspective. This leads to novel protocols in which sensors cooperatively trade off performance with energy consumption with low communication and complexity overhead. Two key results are an on-line adaptive learning algorithm for tracking the correlated equilibrium set of a slowly varying sensor deployment game, and an analysis of the equilibrium properties of threshold policies in a game with noisy, correlated measurements. Finally, the problem of dynamic spectrum access for systems of cognitive radios is considered. A game theoretic formulation leads to a scheme for competitive bandwidth allocation which respects radios' individual interests while enforcing fairness between users. An on-line adaptive learning scheme is again proposed for negotiating fair, equilibrium resource allocations, while dynamically adjusting to changing conditions.
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Attribution-NonCommercial-NoDerivatives 4.0 International