• DocumentCode
    938403
  • Title

    Performance of data-dependent superimposed training without cyclic prefix

  • Author

    McLernon, D.C. ; Alameda-Hernández, E. ; Orozco-Lugo, A.G. ; Lara, M.M.

  • Author_Institution
    Sch. of Electron. & Electr. Eng., Univ. of Leeds, UK
  • Volume
    42
  • Issue
    10
  • fYear
    2006
  • fDate
    5/11/2006 12:00:00 AM
  • Firstpage
    604
  • Lastpage
    606
  • Abstract
    A recent improvement in superimposed training for channel estimation, where the training sequence is actually added to the information data, is called data-dependent superimposed training (DDST). Here we show (theoretically and via simulations) that the performance of DDST (both for channel estimation and equalisation) may suffer minimal degradation when implemented without the use of a cyclic prefix (which carries only redundant information).
  • Keywords
    channel estimation; equalisers; DDST; channel estimation; cyclic prefix; data-dependent superimposed training; degradation; equalisation; information data; training sequence;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el:20060127
  • Filename
    1633584
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=938403