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

• Published in: IET communications Vol. 11; no. 14; pp. 2228 - 2235
• Main Authors: Deng, Qian, Guo, Li, Dong, Chao, Lin, Jiaru, Meng, Dedan, Chen, Xueyan
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 28.09.2017
• Subjects: approximation theory; base station antenna; BS antennas; channel estimates; channel estimation; convergence; convergence rate; detection performance; fast matrix inversion updates; high‐throughput signal detection; matrix approximation; matrix decomposition; matrix inversion; matrix inversion recomputations; MIMO communication; optimal coefficients; optimal iterative initial solution; optimal relaxation parameter; polynomial matrices; Research Article; signal detection; small perturbation; update detection algorithms; uplink massive multiuser multiple‐input multi‐output systems; user terminal antenna; zero‐forcing detector; zero‐forcing matrix decomposition polynomial expansion update; zero‐forcing successive over relaxation update; ZF‐MDPE‐update algorithm; ZF‐SOR‐update algorithms; optimal relaxation parameter; convergence; detection performance; ZF-MDPE-update algorithm; matrix decomposition; polynomial matrices; matrix inversion recomputations; high-throughput signal detection; fast matrix inversion updates; MIMO communication; zero-forcing detector; approximation theory; ZF-SOR-update algorithms; signal detection; small perturbation; matrix inversion; zero-forcing successive over relaxation update; optimal coefficients; matrix approximation; channel estimates; user terminal antenna; zero-forcing matrix decomposition polynomial expansion update; channel estimation; optimal iterative initial solution; BS antennas; uplink massive multiuser multiple-input multi-output systems; update detection algorithms; convergence rate; base station antenna
• ISSN: 1751-8628; 1751-8636
• DOI: 10.1049/iet-com.2016.0743

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, $\beta $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.