Secrecy Rate Region Maximization for Multi-User MIMO Systems with Artificial Noise and Service Integration

This paper considers an artificial noise (AN)-aided transmit design for multi-user MIMO systems with integrated services. Specifically, two sorts of service messages are combined and serve simultaneously: one multicast message intended for all receivers and one confidential message intended for only one receiver. The confidential message is kept perfectly secure from all the unauthorized receivers. Our goal is to jointly design the input covariances for the multicast message, confidential message and AN, such that the achievable secrecy rate region is maximized subject to the sum power constraint. This problem is a vector optimization problem and inherently complex to solve. To find its Pareto boundary, the method of scalarization is used to transform it into an equivalent scalar optimization problem. Nonetheless, this scalar optimization problem is nonconvex and appears to he difficult especially in our considered scenario. Then we show that this problem can be handled by resorting to an alternating optimization (AO) algorithm. The merit of this AO algorithm lies in its provable convergence to one stationary point. Numerical results are finally presented to show the efficacy of our proposed method.