A Novel RZF Precoding Method Based on Matrix Decomposition: Reducing Complexity in Massive MIMO Systems

Qian DENG; Li GUO; Jiaru LIN; Zhihui LIU

doi:10.1587/transcom.2015EBP3251

A Novel RZF Precoding Method Based on Matrix Decomposition: Reducing Complexity in Massive MIMO Systems

Qian DENG, Li GUO, Jiaru LIN, Zhihui LIU

Full Text Views

0

Share
Cite this

Summary :

In this paper, we propose an efficient regularized zero-forcing (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 (β). This approach can speed-up the convergence to the matrix inverse by a matrix polynomial with small terms and further reduce computation costs. Simulation results show that the MDPE 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 β and SNR situations. It thereby obtains a high average achievable rate of the UTs under power allocation.

Publication: IEICE TRANSACTIONS on Communications Vol.E99-B No.2 pp.439-446

Publication Date: 2016/02/01

Publicized

Online ISSN: 1745-1345

DOI: 10.1587/transcom.2015EBP3251

Type of Manuscript: PAPER

Category: Antennas and Propagation

Authors

Qian DENG
  Beijing University of Posts and Telecommunications,Jiangxi University of Science and Technology
Li GUO
  Beijing University of Posts and Telecommunications
Jiaru LIN
  Beijing University of Posts and Telecommunications
Zhihui LIU
  Beijing University of Posts and Telecommunications

Keyword

massive MIMO, matrix decomposition, RZF precoding, computational complexity, power allocation

Cite this

Copy

Qian DENG, Li GUO, Jiaru LIN, Zhihui LIU, "A Novel RZF Precoding Method Based on Matrix Decomposition: Reducing Complexity in Massive MIMO Systems" in IEICE TRANSACTIONS on Communications, vol. E99-B, no. 2, pp. 439-446, February 2016, doi: 10.1587/transcom.2015EBP3251.
Abstract: In this paper, we propose an efficient regularized zero-forcing (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 (β). This approach can speed-up the convergence to the matrix inverse by a matrix polynomial with small terms and further reduce computation costs. Simulation results show that the MDPE 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 β and SNR situations. It thereby obtains a high average achievable rate of the UTs under power allocation.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.2015EBP3251/_p

Copy

@ARTICLE{e99-b_2_439,
author={Qian DENG, Li GUO, Jiaru LIN, Zhihui LIU, },
journal={IEICE TRANSACTIONS on Communications},
title={A Novel RZF Precoding Method Based on Matrix Decomposition: Reducing Complexity in Massive MIMO Systems},
year={2016},
volume={E99-B},
number={2},
pages={439-446},
abstract={In this paper, we propose an efficient regularized zero-forcing (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 (β). This approach can speed-up the convergence to the matrix inverse by a matrix polynomial with small terms and further reduce computation costs. Simulation results show that the MDPE 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 β and SNR situations. It thereby obtains a high average achievable rate of the UTs under power allocation.},
keywords={},
doi={10.1587/transcom.2015EBP3251},
ISSN={1745-1345},
month={February},}

Copy

TY - JOUR
TI - A Novel RZF Precoding Method Based on Matrix Decomposition: Reducing Complexity in Massive MIMO Systems
T2 - IEICE TRANSACTIONS on Communications
SP - 439
EP - 446
AU - Qian DENG
AU - Li GUO
AU - Jiaru LIN
AU - Zhihui LIU
PY - 2016
DO - 10.1587/transcom.2015EBP3251
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E99-B
IS - 2
JA - IEICE TRANSACTIONS on Communications
Y1 - February 2016
AB - In this paper, we propose an efficient regularized zero-forcing (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 (β). This approach can speed-up the convergence to the matrix inverse by a matrix polynomial with small terms and further reduce computation costs. Simulation results show that the MDPE 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 β and SNR situations. It thereby obtains a high average achievable rate of the UTs under power allocation.
ER -