Non-cooperative optimal game-theoretic opportunistic dynamic spectrum access
This paper considers the problem of competitive sharing of open spectrum resources between collocated spread spectrum based secondary systems. The problem is formulated as a strategic form game where the objective of each player (secondary system) is to maximize its own payoff defined in terms of resource utilizations. The necessary and sufficient conditions for the existence of the optimal Nash equilibrium solution are derived for the specified payoff functions. Using tools of the non-cooperative game theory, the Payoff-Enriched Adaptive Learning (PEAL) methodology is proposed to enable each secondary system to iteratively adapt spectrum access strategy in response to the observed interference from other secondary systems. The self-learning adaptations of PEAL require neither signaling nor time synchronization between autonomous secondary systems. It is shown through extensive numerical evaluations that the PEAL adaptations converge to the theoretical Nash equilibrium in a finite numbers of trials.