Decision-aided Jacobi iteration for signal detection in massive MIMO systems

Abstract

Massive MIMO with high spectral efficiency is one of the key technologies for future 5G wireless communications. For signal detection in such systems, a decision-aided Jacobi (DA-Jacobi) iteration is proposed, which can improve the convergence speed as compared with the conventional Jacobi iteration for calculating the result of the linear minimum mean-squared error (MMSE) detection, and, at the same time, can come with lower computational complexity. Simulation results confirm these advantages and demonstrate that the error-rate performance of the proposed DA-Jacobi iteration can be even better than that of the exact linear MMSE detection.