• DocumentCode
    1551614
  • Title

    Efficient adaptive complex filtering algorithm with application to channel equalisation

  • Author

    Perry, R. ; Bull, D.R. ; Nix, A.

  • Author_Institution
    Centre for Commun. Res., Bristol Univ., UK
  • Volume
    146
  • Issue
    2
  • fYear
    1999
  • fDate
    8/1/1999 12:00:00 AM
  • Firstpage
    57
  • Lastpage
    64
  • Abstract
    The paper describes a means of efficiently implementing an adaptive complex transversal filter. Three real-coefficient filter sections are used to realise the transversal filter section of a complex equaliser, thus using one less filter than a conventional realisation. An adaptive algorithm is developed, in a manner similar to the least mean square algorithm, which allows the three filters to be trained independently and in parallel using real valued arithmetic. In this way, the throughput can be maintained, whilst reducing the number of multipliers in both the filter and coefficient update sections by 25%. Using independence theory, it is demonstrated that the three filters converge to a solution consistent with the optimal Wiener-Hopf solution. The convergence speed is characterised in terms of the complex input data stream. The transient behaviour of the algorithm is examined using a simulation of a channel equaliser and is supported by analysis
  • Keywords
    adaptive equalisers; adaptive filters; adaptive signal processing; convergence of numerical methods; digital arithmetic; adaptive algorithm; adaptive complex transversal filter; channel equalisation; coefficient update; complex input data stream; convergence speed; efficient adaptive complex filtering algorithm; gradient based training algorithm; independence theory; least mean square algorithm; multipliers; optimal Wiener-Hopf solution; real valued arithmetic; real-coefficient filter sections; simulation; throughput; transient behaviour;
  • fLanguage
    English
  • Journal_Title
    Vision, Image and Signal Processing, IEE Proceedings -
  • Publisher
    iet
  • ISSN
    1350-245X
  • Type

    jour

  • DOI
    10.1049/ip-vis:19990160
  • Filename
    788761