Alternating Optimization for MIMO Secrecy Channel with a Cooperative Jammer

This paper proposes an alternating optimization algorithm for addressing the secrecy rate optimization problem for a multi-input-multi- output (MIMO) secrecy channel in the presence of a multiantenna eavesdropper, where a multiantenna cooperative jammer will be employed to confuse the eavesdropper by introducing jamming signal. We investigate the secrecy rate maximization problem, which is a non-convex problem in terms of transmit covariance matrices of the legitimate transmitter and the cooperative jammer. In order to circumvent this issue, we develop an optimization algorithm by alternating optimizing the transmit covariance matrices of the legitimate transmitter and the cooperative jammer where each transmit covariance matrix is optimized while other is fixed. Based on this algorithm, we develop a robust scheme by incorporating channel uncertainties associated with the eavesdropper. By exploiting S-Procedure, we show that these robust optimization problems can be formulated into semidefinite programming (SDP). Simulation results have been provided to validate the convergence and the performance of the alternating algorithm.