Low Complexity Signal Detection for Massive MIMO in B5G Uplink System

Massive Multiple Input Multiple Output (M-MIMO) is realized as a mandatory technique for Beyond Fifth Generation (B5G) wireless networks. In next-generation node B (gNB) uplink transmission, M-MIMO requires a low-complexity signal detection scheme with an increased number of antennas to attain high channel capacity and reliability. To attain close-optimal performance in these B5G systems, the Minimum Mean Square Error (MMSE) detection scheme is preferred at the gNB but it demands a complex matrix inversion concerning the number of users. Hence, this article proposes a Modified Weighted Two Stage (MWTS) iterative algorithm with an appropriate initial solution to realize MMSE detection at reduced complexity. MWTS detection algorithm is formulated by integrating the first half iteration phase of the weighted two-stage with the previous phase and ignoring the second half iteration. Further to improve the performance of the B5G system, a low-complexity soft decision Viterbi decoder is introduced at gNB. With K users, the proposed modifications display a reduction in computational complexity of 4K(2)+16K as compared to the weighted two-stage algorithm of 7K(2)+8K. Simulation results confirm that the proposed MWTS algorithm yields lower complexity and near-optimal performance close to MMSE detection.