Title :
Low-complexity signal detection based on relaxation iteration method in massive MIMO systems
Author :
Ruohan Guo ; Xiaohui Li ; Weihong Fu ; Yongqiang Hei
Author_Institution :
Xidian Univ., Xi´an, China
fDate :
12/1/2015 12:00:00 AM
Abstract :
Minimum mean square error (MMSE) detection algorithm can achieve nearly optimal performance when the number of antennas at the base station (BS) is large enough compared to the number of users. But the traditional MMSE involves complicated matrix inversion. In this paper, we propose a modified MMSE algorithm which exploits the channel characteristics occurring in massive multiple-input multiple-output (MIMO) channels and the relaxation iteration (RI) method to avoid the matrix inversion. A proper initial solution is given to accelerate the convergence speed. In addition, we point out that the channel estimation scheme used in channel hardening-exploiting message passing (CHEMP) receiver is very appropriate for our proposed detection algorithm. Simulation results verify that the proposed algorithm can achieve very close performance of the traditional MMSE algorithm with a small number of iterations.
Keywords :
MIMO communication; channel estimation; iterative methods; least mean squares methods; matrix algebra; signal detection; BS; CHEMP receiver; MIMO channels; MMSE detection algorithm; base station; channel estimation scheme; channel hardening-exploiting message passing; complicated matrix inversion; low complexity signal detection; massive MIMO systems; massive multiple-input multiple-output channels; matrix inversion; minimum mean square error; optimal performance; relaxation iteration method; Algorithm design and analysis; Approximation algorithms; Channel estimation; Computational complexity; Convergence; MIMO; channel estimation; massive MIMO detection; minimum mean square error; relaxation iteration;
Journal_Title :
Communications, China
DOI :
10.1109/CC.2015.7386155