Secure Multicast Transmission for Massive MIMO With Statistical Channel State Information

Abstract

We investigate physical layer security in massive multiple-input multiple-output multicast transmission where the base station only knows the statistical channel state information of the legitimate user terminals and the eavesdropper. We first introduce a tight lower bound of the achievable secrecy multicast rate as the design objective. Then, we find the closed-form transmit directions, i.e., the eigenvectors of the optimal multicast transmit covariance matrix, which simplifies the matrix-valued multicast transmit strategy design into a beam domain power allocation problem. We further propose an efficient iterative power allocation algorithm with guaranteed convergence to a local optimal solution by invoking the concave-convex procedure. We also derive the deterministic equivalent of the optimization objective to reduce the computation complexity. Numerical results demonstrate the performance gains of the proposed approach over the conventional approach.