Paper Info
Title
A Low-Complexity Precoding Method Based on the Steepest Descent Algorithm for Downlink Massive MIMO Systems
Abstract
Massive multiple-input multiple-output (MIMO) is one of the key technologies for the fifth generation (5G) due to its high throughput and spectral efficiency. However, the large-size antenna configurations in massive MIMO systems incur significantly high complexity for the conventional linear precoding schemes like minimum mean square error (MMSE) due to the associated high-dimensional matrix inversion operation. To solve the issue, we propose to utilize the steepest descent (SD) algorithm to realize the MMSE precoding operation deprived of the complex matrix inversion. Furthermore, we introduce a weighted-step approach, named weighted SD (WSD), to speed up the convergence process. The convergence of the proposed WSD-based approach is analyzed in this work. Numerical results illustrate that the WSD-based approach outperforms the Neumann-series (NS) based one in terms of the convergence speed and obtains nearly the same performance of the classical MMSE based one with significantly reduced computational complexity.
Year
DOI
Venue
2018
10.1109/ICCChina.2018.8641245
2018 IEEE/CIC International Conference on Communications in China (ICCC)
Keywords
Field
DocType
Massive multiple-input multiple-output (MIMO),minimum mean square error (MMSE),weighted steepest descent (WSD),convergence
Convergence (routing),Gradient descent,Computer science,Minimum mean square error,Algorithm,MIMO,Real-time computing,Spectral efficiency,Precoding,Telecommunications link,Computational complexity theory
Conference
ISSN
ISBN
Citations 
2377-8644
978-1-5386-7005-7
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Yuanyuan Dong101.69
Zhenyu Zhang2176.80
Chen Liang312618.00
Xiaoxiao Yin400.34
Xiyuan Wang511915.30
Runmin Zou6235.73
Xiaoming Dai710021.23