A Noncooperative Spectrum Sensing Game with Maximum Network Throughput

In this paper, we consider a noncooperative cognitive radio network with M selfish secondary users (SUs) opportunistically access N licensed channels. Every SU chooses one channel to sense and subsequently compete to access (based on the sensing outcome) to obtain the channel utility. Different channels may have different utilities. Each SU selfishly makes a sensing decision to maximize its obtained utility. The objective is to design an optimal sensing policy with maximum network throughput. This problem is formulated as a noncooperative game where a stable sensing policy reaches a Nash equilibrium (NE). A novel greedy algorithm with great efficiency is proposed to calculate all pure-strategy NE for a large class of utility functions. By slight modification, the algorithm is able to reach an optimal pure-strategy NE with the maximum network throughput. The algorithm can be practically implemented as a MAC protocol in a distributed way with negligible communication overhead.