Low complexity detection based on RTS method for large-scale MIMO systems

Yingcheng Xu; Linbo Zhang; Tong Liu

doi:10.1117/12.2557581

3 January 2020 Low complexity detection based on RTS method for large-scale MIMO systems

Yingcheng Xu, Linbo Zhang, Tong Liu

Proceedings Volume 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019); 1137337 (2020) https://doi.org/10.1117/12.2557581
Event: Eleventh International Conference on Graphics and Image Processing, 2019, Hangzhou, China

Abstract

For uplink massive MIMO systems with hundreds of antennas at the base station, the Linear Minimum Mean Square Error (MMSE) signal detection algorithm is near optimal but involves matrix inversion with high complexity. In this paper, we proposed a low complexity detection algorithm in uplink large-scale MIMO based on Reactive Tabu Search (RTS) algorithm by using SOR iterative algorithm as the initial solution vector algorithm. The simulation result shows that it can reduce the computational complexity from ο(K³) to ο(K²), where K is the number of users. Under the premise of BER performance of the original algorithm, the simulation result shows that the performance of SOR-RTS method is always close to the original RTS algorithm.

Citation Download Citation

Yingcheng Xu, Linbo Zhang, and Tong Liu "Low complexity detection based on RTS method for large-scale MIMO systems", Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 1137337 (3 January 2020); https://doi.org/10.1117/12.2557581

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available