A Low-Complexity Signal Detection Utilizing AOR Iterative Method for Massive MIMO Systems

Massive multiple-input multiple-output（MIMO） system is capable of substantially improving the spectral efficiency as well as the capacity of wireless networks relying on equipping a large number of antenna elements at the base stations. However, the excessively high computational complexity of the s...

Full description

Saved in:
Bibliographic Details
Published in:China communications 2017-11, Vol.14 (11), p.269-278
Main Authors: Zhang, Zhenyu, Dai, Xiaoming, Dong, Yuanyuan, Wang, Xiyuan, Liu, Tong
Format: Article
Language:English
Subjects:
accelerated overrelaxation (AOR) iterative method
complexity
Computational complexity
Convergence
Iterative methods
Massive MIMO
massive multiple-input multiple-output (MIMO)
minimum mean square error (MMSE)
Signal detection
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Massive multiple-input multiple-output（MIMO） system is capable of substantially improving the spectral efficiency as well as the capacity of wireless networks relying on equipping a large number of antenna elements at the base stations. However, the excessively high computational complexity of the signal detection in massive MIMO systems imposes a significant challenge for practical hardware implementations. In this paper, we propose a novel minimum mean square error（MMSE） signal detection using the accelerated overrelaxation（AOR） iterative method without complicated matrix inversion, which is capable of reducing the overall complexity of the classical MMSE algorithm by an order of magnitude. Simulation results show that the proposed AOR-based method can approach the conventional MMSE signal detection with significant complexity reduction.
ISSN:1673-5447
DOI:10.1109/CC.2017.8233666