A new reduced complexity ML detection scheme for MIMO systems

Jin Sung Kim, Sung Hyun Moon, Inkyu Lee

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

    3 Citations (Scopus)

    Abstract

    For multiple-input multiple-output (MIMO) systems, the optimum maximum likelihood (ML) detection requires tremendous complexity as the number of antennas or modulation level increases. This paper proposes a new algorithm which attains the ML performance with significantly reduced complexity. Based on the minimum mean square error (MMSE) criterion, the proposed scheme reduces the search space by excluding unreliable candidate symbols in data streams. Utilizing the probability metric which evaluates the reliability with the normalized likelihood functions of each symbol candidate, near optimal ML detection is made possible. A threshold parameter is introduced to balance a tradeoff between complexity and performance. Besides, we propose an efficient way of generating the log likelihood ratio (LLR) values which can be used for coded systems.

    Original languageEnglish
    Title of host publicationProceedings - 2009 IEEE International Conference on Communications, ICC 2009
    DOIs
    Publication statusPublished - 2009
    Event2009 IEEE International Conference on Communications, ICC 2009 - Dresden, Germany
    Duration: 2009 Jun 142009 Jun 18

    Publication series

    NameIEEE International Conference on Communications
    ISSN (Print)0536-1486

    Other

    Other2009 IEEE International Conference on Communications, ICC 2009
    Country/TerritoryGermany
    CityDresden
    Period09/6/1409/6/18

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Electrical and Electronic Engineering

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