Performance of overloaded MIMO-OFDM system with repetition code

Hikari Matsuoka, Yoshihito Doi, Tatsuro Yabe, Yukitoshi Sanada

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    4 Citations (Scopus)

    Abstract

    This paper investigates the performance of an overloaded multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system with a repetition code. It has been demonstrated that diversity with block coding prevents the performance degradation induced by signal multiplexing. However, the computational complexity of a joint decoding scheme increases exponentially with the number of multiplexed signal streams. Thus, this paper proposes the use of a repetition code in the overloaded MIMO-OFDM system. In addition, QR decomposition with M-algorithm (QRM) maximum likelihood decoding (MLD) is applied to the decoding of the repetition code. QRM-MLD significantly reduces the amount of joint decoding complexity. In addition, virtual antennas are employed in order to increase the throughput that is reduced by the repetition code. It is shown that the proposed scheme reduces the complexity by about 1/48 for 6 signal streams with QPSK modulation while the BER degradation is less than 0.ldB at the BER of 10-3.

    Original languageEnglish
    Title of host publication2014 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2014
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages239-244
    Number of pages6
    ISBN (Print)9781479961207
    DOIs
    Publication statusPublished - 2014 Jan 27
    Event2014 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2014 - Kuching, Sarawak, Malaysia
    Duration: 2014 Dec 12014 Dec 4

    Other

    Other2014 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2014
    Country/TerritoryMalaysia
    CityKuching, Sarawak
    Period14/12/114/12/4

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Networks and Communications
    • Signal Processing

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