Paper Info
Title
A Fast-Convergent Detector Based on Joint Jacobi and Richardson Method for Uplink Massive MIMO Systems
Abstract
Minimum mean squared error (MMSE) detector achieves near-optimal error rate performance for massive multiple-input multiple-output (M-MIMO) systems but involves large-scale matrix inversion operations with high complexity. Therefore, several approximated matrix inversion algorithms have been proposed. However, their convergence turns out to be very slow. In this paper, a new approach based on joint Jacobi and Richardson method is proposed. We show that the proposed method accelerate the convergence rate at low-complexity for different base station (BS)-to-user-antenna ratio (BUAR). Moreover, a promising initial estimate is utilized to achieve closer-to-optimal initialization for the proposed method. To further accelerate the convergence rate, we introduce a new approximated-eigenvalue based relaxation parameter. The convergence proof of the proposed algorithm is also provided in this work. We analyze the computational complexity of different methods and demonstrate the performance differences with numerical simulations.
Year
DOI
Venue
2019
10.1109/WOCC.2019.8770631
2019 28th Wireless and Optical Communications Conference (WOCC)
Keywords
Field
DocType
―Massive multiple-input multiple-output (MIMO),low-complexity,relaxation parameter,Jacobi iteration,Richardson iteration
Convergence (routing),Approximation algorithm,Matrix (mathematics),Computer science,Word error rate,Minimum mean square error,Algorithm,Electronic engineering,Rate of convergence,Initialization,Computational complexity theory
Conference
ISSN
ISBN
Citations 
2379-1268
978-1-7281-0661-8
0
PageRank 
References 
Authors
0.34
14
7
Name
Order
Citations
PageRank
Imran Ali Khoso100.34
Talha Bin Javed200.34
Shanshan Tu301.01
Yuanyuan Dong401.69
Hua Li535875.80
Xiyuan Wang611915.30
Xiaoming Dai710021.23