skip to main content
10.1145/3290420.3290427acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiccipConference Proceedingsconference-collections
research-article

An improved AOR-based precoding for massive MIMO systems

Published: 02 November 2018 Publication History

Abstract

Compared with traditional multiple-input-multiple-output (MIMO) systems, the number of base station (BS) antennas increased in massive MIMO systems. However, due to the huge number of antennas, linear precoding schemes are able to achieve the near-optimal performance. Conventional linear precoding schemes such as regularized zero forcing (RZF) precoding need to calculate the matrix inversion of large size which leads to high computational complexity. Although utilizing iterative algorithm approximate instead of matrix inversion can reduce the complexity, it leads to slow convergence or general bit error rate (BER) performance. To solve this problem, we proposes a linear precoding scheme based on the accelerated over relaxation (AOR) method. Moreover, we propose a simple way to choose the optimal accelerate factor so that it is only related to the system parameters and more suitable for practical application. Simulation results prove that the improved AOR-based precoding could convergence faster and had better performance of bit error rate (BER).

References

[1]
L Lu, G Li, A Swindlehurst, A Ashikhmin and R Zhang. 2014. An overview of massive MIMO: Benefits and challenges. IEEE J. Sel. Topics Signal Process. pp.742--758.
[2]
Z Zhang, X Wang, K Long, A V Vasilakos and L Hanzo. 2015. Large-scale MIMO-based wireless backhaul in 5G networks. IEEE Wireless Communications. pp.58--66.
[3]
F Boccardi, R W Heath, A Lozano, T L Marzetta and P Popovski. 2014. Five disruptive technology directions for 5G. IEEE Communications Magazine. pp.74--80.
[4]
F Rusek, D Persson, B K Lau, E G Larsson, T L Marzetta, O Edfors and F Tufvesson. 2013. Scaling up MIMO: Opportunities and challenges with very large arrays. IEEE Signal Process. Mag. pp.40--60.
[5]
X Gao, L Dai, Y Hu, Y Zhang and Z Wang. 2015. Low-Complexity Signal Detection for Large Scale MIMO in Optical Wireless Communications. IEEE Journal on Selected Areas in Communications. pp.1903--1912.
[6]
T Xie, Q Han, H Xu, Z Qi and W Shen. 2015. A Low-Complexity Linear Precoding Scheme Based on SOR Method for Massive MIMO Systems. 2015 IEEE 81st Vehicular Technology Conference (VTC Spring). pp.1--5.
[7]
L Dai, X Gao, X Su, S Han, C I and Z Wang. 2015. Low-complexity soft output signal detection based on Gauss-Seidel method for uplink multiuser large-scale MIMO systems. IEEE Trans. Veh. Technol. pp. 4839--4845.
[8]
T Xie, L Dai, X Gao, X Dai and Y Zhao. 2016. Low-Complexity SSOR-Based Precoding for Massive MIMO Systems. IEEE Communications Letters. pp.744--747.
[9]
H Prabhu, J Rodrigues, O Edfors and F Rusek. 2013. Approximative matrix inverse computations for very-large MIMO and applications to linear precoding systems. IEEE Wireless Commun. Netw. Conf. (WCNC). pp. 2710--2715.
[10]
A Hadjidimos. 1978. Accelerated over relaxation method. Mathematies of Computation. pp.147--157.
[11]
Z Zhang, X Dai, Y Dong, X Wang and T Liu. 2017. A Low-Complexity Signal Detection Utilizing AOR Iterative Method for Massive MIMO Systems. China Communications. pp.269--278.
[12]
C B Peel, B M Hochwald and A L Swindlehurst. 2005. A vector-perturbation technique for near-capacity multiantenna multiuser communication-part I: channel inversion and regularization. IEEE Transactions on Communications. pp.195--202.
[13]
Q Xue. 2006. The analysis of the convergence of the AOR method and the comparison with the SOR method. Numerical Mathematics A Journal of Chinese Universities. pp.39--49.
[14]
L Dai, Z Wang and Z Yang. 2013. Spectrally efficient time-frequency training OFDM for mobile large-scale MIMO systems. IEEE Journal on Selected Areas in Communications. pp.251--263.
[15]
Z Lu, J Ning and Y Zhang. 2015. Richardson Method Based Linear Precoding with Low Complexity for Massive MIMO Systems. IEEE Vehicular Technology Conference. pp.1--4.
[16]
Z Bai and J W Silverstein. 2010. Spectral Analysis of Large Dimensional Random Matrices. Springer New York.

Cited By

View all
  • (2024)Unraveling the Efficiency of Multi-user Massive MIMO Precoding Techniques in Millimeter Wave Frequency BandsAdvances in Distributed Computing and Machine Learning10.1007/978-981-97-1841-2_25(325-345)Online publication date: 18-Jun-2024
  • (2021)Efficient Iterative Linear Precoding Scheme for Downlink Massive MIMO SystemsUbiquitous Intelligent Systems10.1007/978-981-16-3675-2_49(631-643)Online publication date: 9-Oct-2021

Index Terms

  1. An improved AOR-based precoding for massive MIMO systems

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ICCIP '18: Proceedings of the 4th International Conference on Communication and Information Processing
    November 2018
    326 pages
    ISBN:9781450365345
    DOI:10.1145/3290420
    • Conference Chairs:
    • Jalel Ben-Othman,
    • Hui Yu,
    • Program Chairs:
    • Herwig Unger,
    • Masayuki Arai
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 02 November 2018

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. linear precoding
    2. massive multiple-input multiple-output (MIMO)
    3. the improved AOR-based precoding

    Qualifiers

    • Research-article

    Funding Sources

    • University Natural Science Research Project of Anhui Province

    Conference

    ICCIP 2018

    Acceptance Rates

    Overall Acceptance Rate 61 of 301 submissions, 20%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)2
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 18 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2024)Unraveling the Efficiency of Multi-user Massive MIMO Precoding Techniques in Millimeter Wave Frequency BandsAdvances in Distributed Computing and Machine Learning10.1007/978-981-97-1841-2_25(325-345)Online publication date: 18-Jun-2024
    • (2021)Efficient Iterative Linear Precoding Scheme for Downlink Massive MIMO SystemsUbiquitous Intelligent Systems10.1007/978-981-16-3675-2_49(631-643)Online publication date: 9-Oct-2021

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media