Radius-adaptive sphere decoding via probabilistic tree pruning

Byonghyo Shim, Insung Kang

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

    6 Citations (Scopus)

    Abstract

    In this paper, we propose a radius-adaptive sphere decoding algorithm that reduces the number of operations in sphere-constrained search while achieving performance close to ML decoding. Specifically, by adding a probabilistic noise constraint on top of sphere constraint, a more stringent necessary condition is provided, particularly at an early stage, and hence many branches that are unlikely to be selected are removed in the early stage of sphere search. From the simulation in a frequency selective channels with pruning probability ε = 0.03, it is shown that the computational complexity of proposed strategy reduces significantly (30-76%) over the original algorithm with negligible performance loss.

    Original languageEnglish
    Title of host publicationSPAWC 2007 - 8th IEEE Workshop on Signal Advances in Wireless Communications
    Publication statusPublished - 2007
    Event8th IEEE Signal Processing Advances in Wireless Communications, SPAWC 2007 - Helsinki, Finland
    Duration: 2007 Jun 172007 Jun 20

    Publication series

    NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC

    Other

    Other8th IEEE Signal Processing Advances in Wireless Communications, SPAWC 2007
    Country/TerritoryFinland
    CityHelsinki
    Period07/6/1707/6/20

    ASJC Scopus subject areas

    • Signal Processing
    • General Engineering

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