Rate Maximization and Beamforming Design for Relay-Aided Multiuser Cognitive Networks

This paper studies the rate maximization problem and designs the beamforming strategy for relay-aided multiuser multiantenna cognitive radio (CR) network that coexists with a primary radio (PR) system via opportunistic spectrum sharing (OSS). The beamforming is characterized by two layers: 1) Cognitive beamforming (CB) is employed by CR base station (BS), CR relay station (RS), and secondary users (SUs) to mitigate the interference to and from the PR. 2) Joint CR-BS and CR-RS beamforming is used to maximize the weighted sum rate of the SUs. Since the optimization turns out to be nonconvex, we apply the classic Blahut-Arimoto algorithm and solve the original problem through an iterative approach. Interestingly, each iterative step involves only convex optimizations whose closed forms can be found. Moreover, we derive an upper bound for the sum rate to assist system analysis. Numerical results show that the proposed approach achieves higher performance, compared with the widely studied diagonally structured beamformer design.