Low-PAPR Approximate Message Passing Precoding Algorithm in Massive MIMO Systems

Meimei MENG; Xiaohui LI; Yulong LIU; Yongqiang HEI

doi:10.1587/transcom.2017EBP3077

Low-PAPR Approximate Message Passing Precoding Algorithm in Massive MIMO Systems

Meimei MENG, Xiaohui LI, Yulong LIU, Yongqiang HEI

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Massive multiple-input and multiple-output (MIMO) is a key technology to meet the increasing capacity demands that must be satisfied by next generation wireless systems. However, it is expensive to use linear power amplifiers when implementing a massive MIMO system as it will have hundreds of antennas. In this paper, considering that low peak-to-average power ratio (PAPR) of transmit signals can facilitate hardware-friendly equipment with nonlinear but power-efficient amplifiers, we first formulate the precoding scheme as a PAPR minimization problem. Then, in order to obtain the optimal solution with low complexity, the precoding problem is recast into a Bayesian estimation problem by leveraging belief propagation algorithm. Eventually, we propose a low-PAPR approximate message passing (LP-AMP) algorithm based on belief propagation to ensure the good transmission performance and minimize the PAPR to realize practical deployments. Simulation results reveal that the proposed method can get PAPR reduction and adequate transmission performance, simultaneously, with low computational complexity. Moreover, the results further indicate that the proposed method is suitable for practical implementation, which is appealing for massive multiuser MIMO (MU-MIMO) systems.

Publication: IEICE TRANSACTIONS on Communications Vol.E101-B No.4 pp.1102-1107

Publication Date: 2018/04/01

Publicized: 2017/09/28

Online ISSN: 1745-1345

DOI: 10.1587/transcom.2017EBP3077

Type of Manuscript: PAPER

Category: Wireless Communication Technologies

Authors

Meimei MENG
  Xidian University
Xiaohui LI
  Xidian University
Yulong LIU
  Xidian University
Yongqiang HEI
  Xidian University

Keyword

massive MU-MIMO, PAPR, MUI, message passing, LP-AMP

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Meimei MENG, Xiaohui LI, Yulong LIU, Yongqiang HEI, "Low-PAPR Approximate Message Passing Precoding Algorithm in Massive MIMO Systems" in IEICE TRANSACTIONS on Communications, vol. E101-B, no. 4, pp. 1102-1107, April 2018, doi: 10.1587/transcom.2017EBP3077.
Abstract: Massive multiple-input and multiple-output (MIMO) is a key technology to meet the increasing capacity demands that must be satisfied by next generation wireless systems. However, it is expensive to use linear power amplifiers when implementing a massive MIMO system as it will have hundreds of antennas. In this paper, considering that low peak-to-average power ratio (PAPR) of transmit signals can facilitate hardware-friendly equipment with nonlinear but power-efficient amplifiers, we first formulate the precoding scheme as a PAPR minimization problem. Then, in order to obtain the optimal solution with low complexity, the precoding problem is recast into a Bayesian estimation problem by leveraging belief propagation algorithm. Eventually, we propose a low-PAPR approximate message passing (LP-AMP) algorithm based on belief propagation to ensure the good transmission performance and minimize the PAPR to realize practical deployments. Simulation results reveal that the proposed method can get PAPR reduction and adequate transmission performance, simultaneously, with low computational complexity. Moreover, the results further indicate that the proposed method is suitable for practical implementation, which is appealing for massive multiuser MIMO (MU-MIMO) systems.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.2017EBP3077/_p

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@ARTICLE{e101-b_4_1102,
author={Meimei MENG, Xiaohui LI, Yulong LIU, Yongqiang HEI, },
journal={IEICE TRANSACTIONS on Communications},
title={Low-PAPR Approximate Message Passing Precoding Algorithm in Massive MIMO Systems},
year={2018},
volume={E101-B},
number={4},
pages={1102-1107},
abstract={Massive multiple-input and multiple-output (MIMO) is a key technology to meet the increasing capacity demands that must be satisfied by next generation wireless systems. However, it is expensive to use linear power amplifiers when implementing a massive MIMO system as it will have hundreds of antennas. In this paper, considering that low peak-to-average power ratio (PAPR) of transmit signals can facilitate hardware-friendly equipment with nonlinear but power-efficient amplifiers, we first formulate the precoding scheme as a PAPR minimization problem. Then, in order to obtain the optimal solution with low complexity, the precoding problem is recast into a Bayesian estimation problem by leveraging belief propagation algorithm. Eventually, we propose a low-PAPR approximate message passing (LP-AMP) algorithm based on belief propagation to ensure the good transmission performance and minimize the PAPR to realize practical deployments. Simulation results reveal that the proposed method can get PAPR reduction and adequate transmission performance, simultaneously, with low computational complexity. Moreover, the results further indicate that the proposed method is suitable for practical implementation, which is appealing for massive multiuser MIMO (MU-MIMO) systems.},
keywords={},
doi={10.1587/transcom.2017EBP3077},
ISSN={1745-1345},
month={April},}

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TY - JOUR
TI - Low-PAPR Approximate Message Passing Precoding Algorithm in Massive MIMO Systems
T2 - IEICE TRANSACTIONS on Communications
SP - 1102
EP - 1107
AU - Meimei MENG
AU - Xiaohui LI
AU - Yulong LIU
AU - Yongqiang HEI
PY - 2018
DO - 10.1587/transcom.2017EBP3077
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E101-B
IS - 4
JA - IEICE TRANSACTIONS on Communications
Y1 - April 2018
AB - Massive multiple-input and multiple-output (MIMO) is a key technology to meet the increasing capacity demands that must be satisfied by next generation wireless systems. However, it is expensive to use linear power amplifiers when implementing a massive MIMO system as it will have hundreds of antennas. In this paper, considering that low peak-to-average power ratio (PAPR) of transmit signals can facilitate hardware-friendly equipment with nonlinear but power-efficient amplifiers, we first formulate the precoding scheme as a PAPR minimization problem. Then, in order to obtain the optimal solution with low complexity, the precoding problem is recast into a Bayesian estimation problem by leveraging belief propagation algorithm. Eventually, we propose a low-PAPR approximate message passing (LP-AMP) algorithm based on belief propagation to ensure the good transmission performance and minimize the PAPR to realize practical deployments. Simulation results reveal that the proposed method can get PAPR reduction and adequate transmission performance, simultaneously, with low computational complexity. Moreover, the results further indicate that the proposed method is suitable for practical implementation, which is appealing for massive multiuser MIMO (MU-MIMO) systems.
ER -