Secure transmission and power allocation in multiuser distributed massive MIMO systems

In this paper, we investigate the secure downlink transmission in a multi-user massive multiple-input multiple-output system assuming there is a passive multi-antenna eavesdropper (Eve) that intends to intercept information of a target user. Specifically, we employ the distributed massive antenna sets at the base station, which are known as remote radio heads (RRHs). With cooperative maximum-ratio transmission beamforming, artificial noise (AN) generation and autonomous power allocation at each RRH, the closed-form deterministic lower bound of the ergodic secrecy rate is derived by random matrix theory. Based on a simplified channel model, the impacts of various parameters on secrecy performance, such as uplink training energy, eavesdropper’s antennas number, power allocation factor, have been analyzed in detail, which provide intuitive insights for optimization and performance evaluation. Moreover, by exploiting complementary geometric programming, an power optimization algorithm over signal and AN power is derived subject to total power and Eve’s signal-to-interference-plus-noise ratio constraints. Numerical results have been presented to reveal the system’s secrecy performance and confirm all analysis results in this paper.