Sequential and Cooperative Sensing for Multi-Channel Cognitive Radios
Effective spectrum sensing is a critical prerequisite for multi-channel Cognitive Radio (CR) networks, where multiple spectrum bands are sensed to identify transmission opportunities, while preventing interference to the primary users. The present paper develops sequential spectrum sensing algorithms which explicitly take into account the sensing time overhead, and optimize a performance metric capturing the effective average data rate of CR transmitters. A constrained dynamic programming problem is formulated to obtain the policy that chooses the best time to stop taking measurements and the best set of channels to access for data transmission, while adhering to hard "Collision" constraints imposed to protect primary links. Given the associated Lagrange multipliers, the optimal access policy is obtained in closed form, and the subsequent problem reduces to an optimal stopping problem.