Complexity reduction in joint decoding of block coded signals in overloaded MIMO-OFDM system

Yoshihito Doi, Mamiko Inamori, Yukitoshi Sanada

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

    3 Citations (Scopus)

    Abstract

    This paper presents a low complexity joint decoding scheme of block coded signals in an overloaded multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. In previous literature, a joint maximum likelihood decoding scheme of block coded signals has been evaluated through theoretical analysis. The diversity gain with block coding prevents performance degradation induced by signal multiplexing. However, the computational complexity of the joint decoding scheme increases exponentially with the number of multiplexed signal streams. Thus, this paper proposes a two step joint decoding scheme for the block coded signals. The first step of the proposed scheme calculates metrics to reduce the number of the candidate codewords using decoding based on joint maximum likehood symbol detection. The second step of the proposed scheme carries out joint decoding on the reduced candidate codewords. It is shown that the proposed scheme reduces the complexity by about 1/174 for 4 signal stream transmission.

    Original languageEnglish
    Title of host publicationISPACS 2013 - 2013 International Symposium on Intelligent Signal Processing and Communication Systems
    Pages590-595
    Number of pages6
    DOIs
    Publication statusPublished - 2013 Dec 1
    Event2013 21st International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2013 - Naha, Okinawa, Japan
    Duration: 2013 Nov 122013 Nov 15

    Publication series

    NameISPACS 2013 - 2013 International Symposium on Intelligent Signal Processing and Communication Systems

    Other

    Other2013 21st International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2013
    CountryJapan
    CityNaha, Okinawa
    Period13/11/1213/11/15

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Signal Processing

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