On Selsh Spectrum Sensing Policy And Congestion Games In Cognitive Radio Network

In this paper, we consider a noncooperative cognitive radio network with M self-ish secondary users (SUs) opportunistically access N licensed channels. Every SUchooses one channel to sense and subsequently compete to access (based on the sens-ing outcome) to obtain the channel utility. Different channels may have different utili-ties. Each SU selfishly makes a sensing decision to maximize its obtained utility. Theobjective is to design an optimal sensing policy with maximum network throughput.This problem is formulated as a noncooperative game where a stable sensing policyreaches a Nash Equilibrium (NE). A novel greedy algorithm with great efficiency isproposed to calculate all pure-strategy NE for a large class of utility functions. Byslight modification, the algorithm is able to reach an optimal pure-strategy NE withthe maximum network throughput. The algorithm can be practically implemented asa MAC protocol in a distributed way with negligible communication overhead. In-tensive simulation experiments verify the correctness of the theorems and reveal theeffectiveness of our algorithm. Furthermore, we have shown that our algorithm canbe extended to all singleton congestion games with strict monotonic utility functions.And for these games, all NE can be calculated within O(n log m).