Energy Harvesting in Secure MIMO Systems

The problems of energy harvesting in wireless communication systems have recently drawn much attention. In this paper, we focus on the investigation of energy harvesting maximization (EHM) in the important secrecy multi-input multioutput (MIMO) systems where little research has been done due to their complexity. Particularly, this paper studies the resource allocation strategies in MIMO wiretap channels, wherein we attempt to maximize the harvested energy by one or multiple multi-antenna energy receivers (ERs) (potential eavesdropper) while guaranteeing the secure communication for the multiantenna information receiver (IR). Two types of IR, with and without the capability to cancel the interference from energy signals, are taken into account. In the scenario of single energy receiver (ER), we consider the joint design of the transmission information and energy covariances for EHM. Both of the optimization problems for the two types of IR are nonconvex, and appear to be difficult. To circumvent them, the combination of first order Taylor approximation and sequential convex optimization approach is proposed. Then, we extend our attention to the scenario with multiple ERs, where the artificial noise (AN) aided weighted sum-energy harvesting maximization (WS-EHM) problem is considered. Other than the approaches adopted in solving the EHM problems, an algorithm conducts in an alternating fashion is proposed to handle this problem. In particular, we first perform a judicious transformation of the WSEHM problem. Then, a block Gauss-Seidel (GS) algorithm based on logarithmic barrier method and gradient projection (GP) is derived to obtain the optimal solution of the reformulation by solving convex problems alternately. Furthermore, the resulting block GS method is proven to converge to a Karush-Kuhn-Tucker (KKT) point of the original WS-EHM problem. Simulation results show the outstanding energy harvesting performance and computational efficiency of our proposed algorithms.