Robust Beamforming for Secrecy Rate in Cooperative Cognitive Radio Multicast Communications

TL;DR

This paper introduces a cooperative beamforming strategy in cognitive radio multicast systems that enhances security by jamming eavesdroppers, maximizing the secondary system's secrecy rate under primary users' constraints.

Contribution

It presents an iterative algorithm to optimize secrecy rate in cognitive radio multicast communications with imperfect channel knowledge and passive eavesdroppers.

Findings

Algorithm converges to a KKT point.

Maximizes secondary secrecy rate while satisfying primary constraints.

Effective in scenarios with imperfect channel information.

Abstract

In this paper, we propose a cooperative approach to improve the security of both primary and secondary systems in cognitive radio multicast communications. During their access to the frequency spectrum licensed to the primary users, the secondary unlicensed users assist the primary system in fortifying security by sending a jamming noise to the eavesdroppers, while simultaneously protect themselves from eavesdropping. The main objective of this work is to maximize the secrecy rate of the secondary system, while adhering to all individual primary users' secrecy rate constraints. In the case of passive eavesdroppers and imperfect channel state information knowledge at the transceivers, the utility function of interest is nonconcave and involved constraints are nonconvex, and thus, the optimal solutions are troublesome. To address this problem, we propose an iterative algorithm to arrive at a local optimum of the considered problem. The proposed iterative algorithm is guaranteed to achieve a Karush-Kuhn-Tucker solution.