Phase Noise Suppression in Uplink Massive MIMO OFDM Systems

Abstract

Massive multiple-input multiple-output (MIMO) is a key technology in next generation wireless communications. However, the presence of phase noise (PHN) is an inevitable factor in degrading the performance of the communication systems. This paper studies the problem of the PHN suppression in the uplink massive MIMO OFDM communication systems. We propose a probabilistic system model and develop a variational expectation maximization (VEM) approach to jointly estimate the data symbols and the PHN sequences. The algorithm works in an iterative manner. By minimizing the Kullback-Leibler (KL) divergence between the joint probability and the posterior probabilities of the PHN sequences and the data symbols, the posterior probabilities of the PHN sequences and data symbols are updated iteratively and the KL divergence ultimately converges to a minimum. The posterior mean of the data symbols obtained in the last iteration will be used for data detection. Furthermore, computational complexity is reduced through some simplifications. At last, the simulation results show that the proposed PHN estimation scheme can improve the performance of the communication systems significantly.