Securing Massive MIMO-NOMA Networks with ZF Beamforming and Artificial Noise

In this paper, we propose using artificial noise (AN) and zero-forcing (ZF) beamforming to protect massive multiple-input multiple-output (MIMO) non- orthogonal multiple access (NOMA) networks. In particular, the ergodic legitimate, eavesdropping, and secrecy rates are derived while taking imperfect channel estimation into account. From the obtained ergodic rates, the effects of ZF precoder, AN, and the number of antennas at the base station are revealed. Results show that the ZF precoder can enhance secrecy performance when compared with maximum ratio transmission precoder. Furthermore, an optimization algorithm is proposed to maximize the sum secrecy rate of the proposed network, while guaranteeing a target secrecy rate at each user equipment. Numerical results verify the correctness of the analysis and the effectiveness of the proposed algorithm.