© The Institution of Engineering and Technology
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.
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Decision-aided Jacobi iteration for signal detection in massive MIMO systems