High-throughput signal detection based on fast matrix inversion updates for uplink massive multiuser multiple-input multi-output systems.

In this study, zero-forcing matrix decomposition polynomial expansion update (ZF-MDPE-update) and zero-forcing successive over relaxation update (ZF-SOR-update) algorithms are proposed to update a zero-forcing detector quickly without requiring complicated matrix inversion recomputations when massive multiple-input multi-output systems channel estimates contain a small perturbation. To further accelerate the convergence rate and to maximise date throughput, a new method of calculating the optimal coefficients for the matrix polynomial that can significantly improve the accuracy of the initial input inverse matrix approximation is considered by the ZF-MDPE-update algorithm. On the other hand, the ZF-SOR-update algorithm with an optimal iterative initial solution and an optimal relaxation parameter is devised, which achieves excellent detection performance. Results demonstrate that when the ratio of base station (BS) antennas to user terminal (UT) antennas, β, is small, the proposed update detection algorithms, with only a few operations, achieve a significant improvement in the average achievable rate of the UTs compared to the recently proposed update algorithm. Therefore, more UTs can be served in a cell with a fixed number of BS antennas. At the same time, the authors' algorithms are shown to facilitate easy memory transfer and are low cost. [ABSTRACT FROM AUTHOR]