Optimal Scheduling of Cooperative Spectrum Sensing in Cognitive Radio Networks

In cognitive radio (CR) networks, secondary users can be coordinated to perform spectrum sensing so as to detect primary user activities more accurately. However, more sensing co-operations for a channel may decrease the transmission time of the secondary users, or lose opportunities for exploiting other channels. In this paper, we study this tradeoff by using the theory of oartially observable Markov decision process (POMDP). This formulation leads to an optimal sensing scheduling policy that determines which secondary users sense which channels with what miss detection probability and false alarm probability. A myopic policy with lower complexity yet comparable performance is also proposed. We further analytically study the properties and the solution structure for the myopic and the optimal policies under a simplified system model. Theoretical results reveal that under certain conditions, some simple but robust structures of the value function exist, which lead to an easy way to obtain the solution of POMDP. Moreover, the cooperative sensing scheduling problem embedded in our POMDP, which is generally a hard combinatorial problem, can be analyzed in an efficient way. Numerical and simulation results are provided to illustrate that our design can utilize the spectrum more efficiently for CR users.