Randomized Strategies for Multi-User Multi-Channel Opportunity Sensing

We show how the expected network throughput of contending secondary users in an opportunistic spectrum access network can be optimized by making appropriate sensing decisions. We consider both uncoordinated symmetric users that see the same primary user behavior, and also a more general coordinated asymmetric setting. For the uncoordinated symmetric case, we show that when the number of users exceeds the number of channels, the optimal strategy is independent of primary user behavior. For the coordinated asymmetric case, we show that at the optimal operation point each user can adopt a pure strategy. Furthermore, the optimal solution can be obtained by using the Hungarian algorithm for bipartite maximum weight matching.