Jointly Optimal Sensing and Resource Allocation for Multiuser Overlay Cognitive Radios

TL;DR

This paper proposes a joint optimization framework for sensing and resource allocation in multiuser overlay cognitive radios, improving efficiency and primary user protection.

Contribution

It introduces a two-step optimal strategy combining dynamic programming and nonlinear optimization for joint sensing and resource allocation.

Findings

The two-step strategy is proven to be optimal.

The approach yields intuitive and effective policies.

Computational complexity is significantly reduced.

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 overlay 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 the primary users. The joint design is addressed using dynamic programming and nonlinear optimization techniques. A two-step strategy that first finds the optimal resource allocation for any sensing scheme and then uses that solution as input to solve for the optimal sensing policy is implemented. 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.