Beam domain secure transmission for massive MIMO communications

TL;DR

This paper explores beam domain transmission strategies for secure massive MIMO systems with passive eavesdroppers, deriving optimal power allocation methods to maximize secrecy rates using statistical channel information.

Contribution

It introduces a new lower bound on the ergodic secrecy sum-rate and develops an efficient algorithm for optimal power allocation in beam domain transmission.

Findings

Beam domain transmission achieves optimal secrecy sum-rate performance.

Power allocation strategies improve secrecy rates by avoiding beams vulnerable to eavesdroppers.

The proposed algorithm converges quickly and approaches optimal performance.

Abstract

We investigate the optimality and power allocation algorithm of beam domain transmission for single-cell massive multiple-input multiple-output (MIMO) systems with a multi-antenna passive eavesdropper. Focusing on the secure massive MIMO downlink transmission with only statistical channel state information of legitimate users and the eavesdropper at base station, we introduce a lower bound on the achievable ergodic secrecy sum-rate, from which we derive the condition for eigenvectors of the optimal input covariance matrices. The result shows that beam domain transmission can achieve optimal performance in terms of secrecy sum-rate lower bound maximization. For the case of single-antenna legitimate users, we prove that it is optimal to allocate no power to the beams where the beam gains of the eavesdropper are stronger than those of legitimate users in order to maximize the secrecy sum-rate lower bound. Then, motivated by the concave-convex procedure and the large dimension random matrix theory, we develop an efficient iterative and convergent algorithm to optimize power allocation in the beam domain. Numerical simulations demonstrate the tightness of the secrecy sum-rate lower bound and the near-optimal performance of the proposed iterative algorithm.