Paper Info
Title
A Novel Rzf Precoding Method Based On Matrix Decomposition: Reducing Complexity In Massive Mimo Systems
Abstract
In this paper, we propose an efficient regularized zeroforcing (RZF) precoding method that has lower hardware resource requirements and produces a shorter delay to the first transmitted symbol compared with truncated polynomial expansion (TPE) that is based on Neumann series in massive multiple-input multiple-output (MIMO) systems. The proposed precoding scheme, named matrix decomposition-polynomial expansion (MDPE), essentially applies a matrix decomposition algorithm based on polynomial expansion to significantly reduce full matrix multiplication computational complexity. Accordingly, it is suitable for real-time hardware implementations and high-mobility scenarios. Furthermore, the proposed method provides a simple expression that links the optimization coefficients to the ratio of BS/UTs antennas (beta). This approach can speedup the convergence to the matrix inverse by a matrix polynomial with small terms and further reduce computation costs. Simulation results show that theMDPE scheme can rapidly approximate the performance of the full precision RZF and optimal TPE algorithm, while adaptively selecting matrix polynomial terms in accordance with the different a and SNR situations. It thereby obtains a high average achievable rate of the UTs under power allocation.
Year
DOI
Venue
2016
10.1587/transcom.2015EBP3251
IEICE TRANSACTIONS ON COMMUNICATIONS
Keywords
Field
DocType
massive MIMO, matrix decomposition, RZF precoding, computational complexity, power allocation
Mimo systems,Computer science,Matrix decomposition,Computer engineering,Precoding,Computational complexity theory,Distributed computing
Journal
Volume
Issue
ISSN
E99B
2
0916-8516
Citations 
PageRank 
References 
1
0.36
7
Authors
4
Name
Order
Citations
PageRank
Qian Deng110.36
Li Guo25818.35
Jiaru Lin364680.74
Zhihui Liu419318.65