In this paper, an energy harvesting scheme for a multi-user
multiple-input-multiple-output (MIMO) secrecy channel with artificial noise
(AN) transmission is investigated. Joint optimization of the transmit
beamforming matrix, the AN covariance matrix, and the power splitting ratio is
conducted to minimize the transmit power under the target secrecy rate, the
total transmit power, and the harvested energy constraints. The original
problem is shown to be non-convex, which is tackled by a two-layer
decomposition approach. The inner layer problem is solved through semi-definite
relaxation, and the outer problem, on the other hand, is shown to be a single-
variable optimization that can be solved by one-dimensional (1- D) line search.
To reduce computational complexity, a sequential parametric convex
approximation (SPCA) method is proposed to find a near-optimal solution. The
work is then extended to the imperfect channel state information case with
norm-bounded channel errors. Furthermore, tightness of the relaxation for the
proposed schemes are validated by showing that the optimal solution of the
relaxed problem is rank-one. Simulation results demonstrate that the proposed
SPCA method achieves the same performance as the scheme based on 1-D but with
much lower complexity.Comment: 12 pages, 6 figures, submitted for possible publicatio