• DocumentCode
    616347
  • Title

    Search space design of enhanced physical downlink control channel for long term evolution advanced system

  • Author

    Liu Liu ; Qin Mu ; Takeda, Kenji ; Lan Chen

  • Author_Institution
    DOCOMO Beijing Commun. Labs. Co., Ltd., Beijing, China
  • fYear
    2013
  • fDate
    7-10 April 2013
  • Firstpage
    3323
  • Lastpage
    3328
  • Abstract
    This paper focuses on investigating the search space design of Enhanced Physical Downlink Control CHannel (EPD-CCH), which is introduced in Long Term Evolution-Advanced (LTE-A) system to increase the capacity of the downlink control channel. Since EPDCCH is frequency-division-multiplexed with downlink data channel, resource utilization efficiency is a very important issue in addition to blocking probability. This paper proposes the innovative methods of locating the search spaces of EPDCCH with different transmission schemes, i.e. distributed transmission and localized transmission, considering the UE complexity, the capacity of control channel and the impacts on Physical Downlink Shared CHannel (PDSCH). By simulation results, it is proven that the proposed methods could get higher resource utilization and lower blocking probability while maintain the same UE complexity in blind decoding.
  • Keywords
    Long Term Evolution; channel capacity; decoding; frequency division multiplexing; radio links; EPDCCH; LTE-A system; Long Term Evolution advanced system; PDSCH; UE complexity; blind decoding; blocking probability; channel capacity; downlink data channel; enhanced physical downlink control channel; frequency division multiplexing; resource utilization; resource utilization efficiency; search space design; Aerospace electronics; Decoding; Downlink; Frequency division multiplexing; Long Term Evolution; Resource management; Time-frequency analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications and Networking Conference (WCNC), 2013 IEEE
  • Conference_Location
    Shanghai
  • ISSN
    1525-3511
  • Print_ISBN
    978-1-4673-5938-2
  • Electronic_ISBN
    1525-3511
  • Type

    conf

  • DOI
    10.1109/WCNC.2013.6555096
  • Filename
    6555096