Jointly Optimal Sensing and Resource Allocation for Multiuser Interweave Cognitive Radios

Abstract

Successful deployment of cognitive radios requires efficient sensing of the spectrum and dynamic adaptation of the available resources according to the sensed (imperfect) information. While most works design these two tasks separately, in this paper we address them jointly. In particular, we investigate an interweave cognitive radio with multiple secondary users that access orthogonally a set of frequency bands originally devoted to primary users. The schemes are designed to minimize the cost of sensing, maximize the performance of the secondary users (weighted sum rate), and limit the probability of interfering with the primary users. The joint design is addressed using nonlinear optimization and dynamic programming, which is able to leverage the time correlation in the activity of the primary network. A two-step strategy is implemented: it first finds the optimal resource allocation for any sensing scheme and then uses that solution as input to solve for the optimal sensing policy. The two-step strategy is optimal, gives rise to intuitive optimal policies, and entails a computational complexity much lower than that required to solve the original formulation.