Biobjective transmitter optimization for service integration in MIMO Gaussian broadcast channel

This paper considers a two-receiver multiple-input multiple-output (MIMO) Gaussian broadcast channel model with integrated services. Specifically, two sorts of service messages are combined and served simultaneously: one multicast message intended for both receivers and one confidential message intended for only one receiver and kept perfectly secure from the other receiver. Our goal is to jointly design the transmit covariances of the multicast message and confidential message, such that the secrecy capacity region is maximized. This maximization problem is a biobjective optimization problem, but can be converted into a general scalar optimization problem via our proposed method of scalarization. Nonetheless, the equivalent scalar problem is nonconvex by nature. To circumvent the nonconvex issue, a provably convergent difference-of-concave (DC) approach is introduced to solve it in an iterative fashion. In view of the high computational complexity of the DC approach, a power splitting method is also devised for fast implementation of service integration. The security performance and computational efficiency of our proposed algorithms are finally demonstrated by numerical results.