Uplink capacity and required transmit power of DS-CDMA DAN

Shohei Inoshita, Hiroyuki Miyazaki, Fumiyuki Adachi

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

    3 Citations (Scopus)

    Abstract

    Antenna diversity is a powerful technique to mitigate the impact of multipath fading. In a conventional centralized antenna network (CAN), diversity antennas are co-located at base station and hence, the impacts of the propagation path loss and the shadowing loss cannot be mitigated. Distributed antenna network (DAN) is an effective way to mitigate all of the above impacts. The choice of the multi-access technique is a very important issue. In this paper, we consider broadband DS-CDMA with joint minimum mean square error based frequency domain-equalization (MMSE-FDE)/antenna diversity as the multi-access technique for DAN and investigate the link capacity and required transmit power to compare with CAN. It is shown by the computer simulation that DS-CDMA DAN can reduce the required transmit power for the given bit error rate (BER) and can obtain larger uplink cellular capacity than DS-CDMA CAN.

    Original languageEnglish
    Title of host publicationISPACS 2013 - 2013 International Symposium on Intelligent Signal Processing and Communication Systems
    Pages797-801
    Number of pages5
    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
    Country/TerritoryJapan
    CityNaha, Okinawa
    Period13/11/1213/11/15

    Keywords

    • CCI
    • DAN
    • DS-CDMA
    • MUI
    • TPC
    • Uplink capacity
    • extended diversity

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Signal Processing

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