A hybrid iterative MIMO detection algorithm: Partial Gaussian approach with integer programming

L. Fang, Lu Xu, Qinghua Guo, David Huang, S.E. Nordholm

    Research output: Chapter in Book/Conference paperConference paper

    Abstract

    © 2014 IEEE. In this paper, after showing MMSE-SIC suffers from performance loss when the channel is spatially correlated for Massive MIMO, we propose an effective hybrid iterative detection algorithm named partial Gaussian approach with integer programming (PGA-IP) to handle correlated channels. In PGA-IP, a partial gaussian approach is first employed to reduce the massive MIMO detection (with large dimension Nt ×Nr MIMO channel) to a problem of marginalizing M (M is a parameter and M蠐 Nt, Nr) discrete valued symbols over an M-degree quadratic function. Then we employ integer programming which is a tree based branch-and-bound search algorithm to further reduce the complexity of the M-dimensional marginalization. Simulation results show that the proposed PGA-IP outperforms MMSE-SIC by about 5dB under heavily correlated channel with only several times of increased computational complexity. At the same time, with about 5% of the complexity of the exact PGA algorithm, the proposed PGA-IP only suffers marginal performance penalty.
    Original languageEnglish
    Title of host publication2014 IEEE/CIC International Conference on Communications in China, ICCC 2014
    Place of PublicationUnited States
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages463-468
    ISBN (Print)9781479941469
    DOIs
    Publication statusPublished - 2014
    Event2014 IEEE/CIC International Conference on Communications in China - Shanghai, China
    Duration: 13 Oct 201415 Oct 2014

    Conference

    Conference2014 IEEE/CIC International Conference on Communications in China
    CountryChina
    CityShanghai
    Period13/10/1415/10/14

    Fingerprint

    Integer programming
    MIMO systems
    Computational complexity

    Cite this

    Fang, L., Xu, L., Guo, Q., Huang, D., & Nordholm, S. E. (2014). A hybrid iterative MIMO detection algorithm: Partial Gaussian approach with integer programming. In 2014 IEEE/CIC International Conference on Communications in China, ICCC 2014 (pp. 463-468). United States: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICCChina.2014.7008322
    Fang, L. ; Xu, Lu ; Guo, Qinghua ; Huang, David ; Nordholm, S.E. / A hybrid iterative MIMO detection algorithm: Partial Gaussian approach with integer programming. 2014 IEEE/CIC International Conference on Communications in China, ICCC 2014. United States : IEEE, Institute of Electrical and Electronics Engineers, 2014. pp. 463-468
    @inproceedings{1d46b89518f8411592e45dd2299b0876,
    title = "A hybrid iterative MIMO detection algorithm: Partial Gaussian approach with integer programming",
    abstract = "{\circledC} 2014 IEEE. In this paper, after showing MMSE-SIC suffers from performance loss when the channel is spatially correlated for Massive MIMO, we propose an effective hybrid iterative detection algorithm named partial Gaussian approach with integer programming (PGA-IP) to handle correlated channels. In PGA-IP, a partial gaussian approach is first employed to reduce the massive MIMO detection (with large dimension Nt ×Nr MIMO channel) to a problem of marginalizing M (M is a parameter and M蠐 Nt, Nr) discrete valued symbols over an M-degree quadratic function. Then we employ integer programming which is a tree based branch-and-bound search algorithm to further reduce the complexity of the M-dimensional marginalization. Simulation results show that the proposed PGA-IP outperforms MMSE-SIC by about 5dB under heavily correlated channel with only several times of increased computational complexity. At the same time, with about 5{\%} of the complexity of the exact PGA algorithm, the proposed PGA-IP only suffers marginal performance penalty.",
    author = "L. Fang and Lu Xu and Qinghua Guo and David Huang and S.E. Nordholm",
    year = "2014",
    doi = "10.1109/ICCChina.2014.7008322",
    language = "English",
    isbn = "9781479941469",
    pages = "463--468",
    booktitle = "2014 IEEE/CIC International Conference on Communications in China, ICCC 2014",
    publisher = "IEEE, Institute of Electrical and Electronics Engineers",
    address = "United States",

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    Fang, L, Xu, L, Guo, Q, Huang, D & Nordholm, SE 2014, A hybrid iterative MIMO detection algorithm: Partial Gaussian approach with integer programming. in 2014 IEEE/CIC International Conference on Communications in China, ICCC 2014. IEEE, Institute of Electrical and Electronics Engineers, United States, pp. 463-468, 2014 IEEE/CIC International Conference on Communications in China, Shanghai, China, 13/10/14. https://doi.org/10.1109/ICCChina.2014.7008322

    A hybrid iterative MIMO detection algorithm: Partial Gaussian approach with integer programming. / Fang, L.; Xu, Lu; Guo, Qinghua; Huang, David; Nordholm, S.E.

    2014 IEEE/CIC International Conference on Communications in China, ICCC 2014. United States : IEEE, Institute of Electrical and Electronics Engineers, 2014. p. 463-468.

    Research output: Chapter in Book/Conference paperConference paper

    TY - GEN

    T1 - A hybrid iterative MIMO detection algorithm: Partial Gaussian approach with integer programming

    AU - Fang, L.

    AU - Xu, Lu

    AU - Guo, Qinghua

    AU - Huang, David

    AU - Nordholm, S.E.

    PY - 2014

    Y1 - 2014

    N2 - © 2014 IEEE. In this paper, after showing MMSE-SIC suffers from performance loss when the channel is spatially correlated for Massive MIMO, we propose an effective hybrid iterative detection algorithm named partial Gaussian approach with integer programming (PGA-IP) to handle correlated channels. In PGA-IP, a partial gaussian approach is first employed to reduce the massive MIMO detection (with large dimension Nt ×Nr MIMO channel) to a problem of marginalizing M (M is a parameter and M蠐 Nt, Nr) discrete valued symbols over an M-degree quadratic function. Then we employ integer programming which is a tree based branch-and-bound search algorithm to further reduce the complexity of the M-dimensional marginalization. Simulation results show that the proposed PGA-IP outperforms MMSE-SIC by about 5dB under heavily correlated channel with only several times of increased computational complexity. At the same time, with about 5% of the complexity of the exact PGA algorithm, the proposed PGA-IP only suffers marginal performance penalty.

    AB - © 2014 IEEE. In this paper, after showing MMSE-SIC suffers from performance loss when the channel is spatially correlated for Massive MIMO, we propose an effective hybrid iterative detection algorithm named partial Gaussian approach with integer programming (PGA-IP) to handle correlated channels. In PGA-IP, a partial gaussian approach is first employed to reduce the massive MIMO detection (with large dimension Nt ×Nr MIMO channel) to a problem of marginalizing M (M is a parameter and M蠐 Nt, Nr) discrete valued symbols over an M-degree quadratic function. Then we employ integer programming which is a tree based branch-and-bound search algorithm to further reduce the complexity of the M-dimensional marginalization. Simulation results show that the proposed PGA-IP outperforms MMSE-SIC by about 5dB under heavily correlated channel with only several times of increased computational complexity. At the same time, with about 5% of the complexity of the exact PGA algorithm, the proposed PGA-IP only suffers marginal performance penalty.

    U2 - 10.1109/ICCChina.2014.7008322

    DO - 10.1109/ICCChina.2014.7008322

    M3 - Conference paper

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    BT - 2014 IEEE/CIC International Conference on Communications in China, ICCC 2014

    PB - IEEE, Institute of Electrical and Electronics Engineers

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    Fang L, Xu L, Guo Q, Huang D, Nordholm SE. A hybrid iterative MIMO detection algorithm: Partial Gaussian approach with integer programming. In 2014 IEEE/CIC International Conference on Communications in China, ICCC 2014. United States: IEEE, Institute of Electrical and Electronics Engineers. 2014. p. 463-468 https://doi.org/10.1109/ICCChina.2014.7008322