Research Article
Low-Complexity MMSE Signal Detection Based on WSSOR Method for Massive MIMO Systems
@INPROCEEDINGS{10.1007/978-3-319-66628-0_19, author={Hua Quan and Silviu Ciocan and Wang Qian and Shen Bin}, title={Low-Complexity MMSE Signal Detection Based on WSSOR Method for Massive MIMO Systems}, proceedings={Communications and Networking. 11th EAI international Conference, ChinaCom 2016 Chongqing, China, September 24-26, 2016, Proceedings, Part II}, proceedings_a={CHINACOM}, year={2017}, month={10}, keywords={Massive MIMO detection Minimum mean square error Weighting symmetric successive over-relaxation}, doi={10.1007/978-3-319-66628-0_19} }- Hua Quan
Silviu Ciocan
Wang Qian
Shen Bin
Year: 2017
Low-Complexity MMSE Signal Detection Based on WSSOR Method for Massive MIMO Systems
CHINACOM
Springer
DOI: 10.1007/978-3-319-66628-0_19
Abstract
Signal detection algorithm based on the linear minimum mean square error (LMMSE) criteria can achieve quasi-optimal performance in uplink of massive MIMO systems where the base stations are equipped with hundreds of antennas. However, it introduces complicated matrix inversion operations, thus making it prohibitively difficult to implement rapidly and effectively. In this paper, we first propose a low complexity signal detection approach by exploiting the weighting symmetric successive over-relaxation (WSSOR) iterative method to circumvent the computations in the matrix inversion. We then present a proper initial solution, relaxation parameter, and scope of the weighting factor to accelerate the convergence speed. Simulation results prove that the proposed simplified method can reach its performance quite close to that of the LMMSE algorithm with no more than three iterations.
