Distributed antenna selection for OFDM space-time block coded diversity

Hiroyuki Miyazaki, Fumiyuki Adachi

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

    2 Citations (Scopus)

    Abstract

    Antenna selection is an important issue for a distributed antenna-based small-cell network (DAN). This paper proposes a distributed antenna (DA) selection for DAN downlink using orthogonal frequency division multiplexing (OFDM) and spacetime block coded (STBC) diversity. The proposed DA selection is an iterative algorithm which determines DA groups (each group consists of DAs communicating with a different user equipment (UE)) to maximize the downlink sum capacity by taking into account co-channel interference (CCI). In each iteration, one DA is added/removed to/from one of current DA groups if this increases the sum capacity by the largest amount. This is repeated until the sum capacity starts to decrease or by the prescribed number of times. It is shown by computer simulation that the proposed DA selection algorithm increases the 10% outage sum capacity by about 20% compared to the received signal power-based DA selection (no CCI is considered).

    Original languageEnglish
    Title of host publication2016 IEEE 84th Vehicular Technology Conference, VTC Fall 2016 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781509017010
    DOIs
    Publication statusPublished - 2016 Jul 2
    Event84th IEEE Vehicular Technology Conference, VTC Fall 2016 - Montreal, Canada
    Duration: 2016 Sep 182016 Sep 21

    Publication series

    NameIEEE Vehicular Technology Conference
    Volume0
    ISSN (Print)1550-2252

    Other

    Other84th IEEE Vehicular Technology Conference, VTC Fall 2016
    Country/TerritoryCanada
    CityMontreal
    Period16/9/1816/9/21

    Keywords

    • Antenna selection
    • Component; Distributed antenna-based small-cell network
    • Space-frequency block coding

    ASJC Scopus subject areas

    • Computer Science Applications
    • Electrical and Electronic Engineering
    • Applied Mathematics

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