Artificial-noise aided transmit design for multi-user MISO systems with integrated services

This paper considers an optimal artificial noise (AN)-aided transmit design for multi-user MISO systems in the eyes of service integration. Specifically, we combine two sorts of services, and serve them 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 optimal 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. To this end, we exploit its hidden convexity and transform the original secrecy rate maximization (SRM) problem into a semidefinite programming. Furthermore, we prove that the optimal input covariance matrix of confidential message is always with rank one, which implies the optimality of beamforming. Numerical results are presented to show the efficacy of our proposed method.