MAX-SLNR Precoding Algorithm for Massive MIMO System

Pilot Contamination obviously degrades the system performance of Massive MIMO systems. In this paper, a downlink precoding algorithm based on the Signal-to- Leakage-plus-Noise-Ratio (SLNR) criterion is put forward. First, the impact of Pilot Contamination on SLNR is analyzed,then the precoding matri...

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Main Authors: Jiang Jing, Wang Honglin, Xie Yongbin, Yang Wujun
Format: Article
Language:English
Published: EDP Sciences 2016-01-01
Series:MATEC Web of Conferences
Online Access:http://dx.doi.org/10.1051/matecconf/20165605005
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author Jiang Jing
Wang Honglin
Xie Yongbin
Yang Wujun
author_facet Jiang Jing
Wang Honglin
Xie Yongbin
Yang Wujun
author_sort Jiang Jing
collection DOAJ
description Pilot Contamination obviously degrades the system performance of Massive MIMO systems. In this paper, a downlink precoding algorithm based on the Signal-to- Leakage-plus-Noise-Ratio (SLNR) criterion is put forward. First, the impact of Pilot Contamination on SLNR is analyzed,then the precoding matrix is calculated with the eigenvalues decomposition of SLNR, which not only maximize the array gains of the target user, but also minimize the impact of Pilot Contamination and the leak to the users of other cells. Further, a simplified solution is derived, in which the impact of Pilot Contamination can be suppressed only with the large-scale fading coefficients. Simulation results reveal that: in the scenario of the serious pilot contamination, the proposed algorithm can avoid the performance loss caused by the pilot contamination compared with the conventional Massive MIMO precoding algorithm. Thus the proposed algorithm can acquire the perfect performance gains of Massive MIMO system and has better practical value since the large-scale fading coefficients are easy to measure and feedback.
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spelling doaj.art-06d6790ccb6541d4a86f518dda740acc2022-12-21T20:02:16ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01560500510.1051/matecconf/20165605005matecconf_iccae2016_05005MAX-SLNR Precoding Algorithm for Massive MIMO SystemJiang JingWang HonglinXie YongbinYang WujunPilot Contamination obviously degrades the system performance of Massive MIMO systems. In this paper, a downlink precoding algorithm based on the Signal-to- Leakage-plus-Noise-Ratio (SLNR) criterion is put forward. First, the impact of Pilot Contamination on SLNR is analyzed,then the precoding matrix is calculated with the eigenvalues decomposition of SLNR, which not only maximize the array gains of the target user, but also minimize the impact of Pilot Contamination and the leak to the users of other cells. Further, a simplified solution is derived, in which the impact of Pilot Contamination can be suppressed only with the large-scale fading coefficients. Simulation results reveal that: in the scenario of the serious pilot contamination, the proposed algorithm can avoid the performance loss caused by the pilot contamination compared with the conventional Massive MIMO precoding algorithm. Thus the proposed algorithm can acquire the perfect performance gains of Massive MIMO system and has better practical value since the large-scale fading coefficients are easy to measure and feedback.http://dx.doi.org/10.1051/matecconf/20165605005
spellingShingle Jiang Jing
Wang Honglin
Xie Yongbin
Yang Wujun
MAX-SLNR Precoding Algorithm for Massive MIMO System
MATEC Web of Conferences
title MAX-SLNR Precoding Algorithm for Massive MIMO System
title_full MAX-SLNR Precoding Algorithm for Massive MIMO System
title_fullStr MAX-SLNR Precoding Algorithm for Massive MIMO System
title_full_unstemmed MAX-SLNR Precoding Algorithm for Massive MIMO System
title_short MAX-SLNR Precoding Algorithm for Massive MIMO System
title_sort max slnr precoding algorithm for massive mimo system
url http://dx.doi.org/10.1051/matecconf/20165605005
work_keys_str_mv AT jiangjing maxslnrprecodingalgorithmformassivemimosystem
AT wanghonglin maxslnrprecodingalgorithmformassivemimosystem
AT xieyongbin maxslnrprecodingalgorithmformassivemimosystem
AT yangwujun maxslnrprecodingalgorithmformassivemimosystem