Secrecy rate maximization for information and energy transfer in MIMO beamforming networks

Consider a multiple-input multiple-output (MIMO) beamforming system, where a multi-antenna base station transmits information and energy simultaneously to a multi-antenna information receiver (IR) and a number of multi-antenna energy receivers (ERs). The ERs are assumed to possess dual functionality such that they can also decode information. This gives rise to the physical layer security issue of providing confidential information to the IR while ensuring efficient energy harvesting for the ERs. Hence, we employ an artificial noise (AN)-aided secrecy approach at the transmitter, where the AN improves the security by interfering with the information decoding at the ERs while, at the same time, providing them with wireless energy to harvest. In this paper, we address the problem of jointly optimizing the beamforming matrix for the IR and the covariance matrix of the AN such that the secrecy rate is maximized subject to energy harvesting constraints and a total power constraint. The corresponding optimization problem is a difference of convex functions (DC) programming problem, which is generally non-convex. Nevertheless, we propose an alternating optimization (AO) strategy to tackle this problem for the cases of a square and a non-square IR channel. The performance of the proposed algorithms is demonstrated by simulation results.