• DocumentCode
    1295213
  • Title

    Adaptive Linear Turbo Equalization Over Doubly Selective Channels

  • Author

    Choi, Jun Won ; Riedl, Thomas J. ; Kim, Kyeongyeon ; Singer, Andrew C. ; Preisig, James C.

  • Author_Institution
    Coordinated Sci. Lab. (CSL), Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • Volume
    36
  • Issue
    4
  • fYear
    2011
  • Firstpage
    473
  • Lastpage
    489
  • Abstract
    Over the last decade, tremendous gains, leading to near-capacity achieving performance, have been shown for a variety of communication systems through the application of the turbo principle, i.e., the exchange of extrinsic information between constituent algorithms for tasks such as channel decoding, equalization, and multiple-input-multiple-output (MIMO) detection. In this paper, we study the practical application of such an iterative detection and decoding (IDD) framework to underwater acoustic communications. We explore complexity and performance tradeoffs of a variety of turbo equalization (TEQ)-based receiver architectures. First, we elaborate on two popular but suboptimal turbo equalization techniques: a channel-estimate-based minimum mean-square error TEQ (CE-based MMSE-TEQ) and a direct-adaptive TEQ (DA-TEQ). We study the behavior of both TEQ approaches in the presence of channel estimation errors and adaptive filter adjustment errors. We confirm that after a sufficient number of iterations, the performance gap between these two TEQ algorithms becomes small. Next, we demonstrate that an underwater receiver architecture built upon the least mean squares (LMS) DA-TEQ technique can leverage and dramatically improve the performance of the conventional implementation based on the decision-feedback equalizer at a feasible complexity. To maintain performance gains over time-varying channels, the slow convergence speed of the LMS algorithm has been improved via two methods: 1) repeating the weight update for the same set of data with decreasing step size and 2) reducing the dimensionality of the equalizer by capturing sparse channel structure. This receiver architecture was used to process collected data from the SPACE 08 experiment (Martha´s Vineyard, MA). Receiver performance for different modulation orders, channel codes, and hydrophone configurations is examined at a variety of distance, up to 1 km from the transmitters. Experimental results show great promise - - for this approach, as data rates in excess of 15 kb/s could readily be achieved without error.
  • Keywords
    MIMO communication; channel coding; channel estimation; decoding; equalisers; hydrophones; least mean squares methods; mean square error methods; radio receivers; MIMO detection; SPACE 08 experiment; TEQ-based receiver; adaptive linear turbo equalization; channel codes; channel decoding; channel-estimate-based minimum mean-square error; decision-feedback equalizer; detection and decoding; direct-adaptive TEQ; doubly selective channels; hydrophone configurations; least mean squares technique; multiple-input-multiple-output detection; Adaptive equalizers; Channel estimation; Decoding; Least squares approximation; Receivers; Underwater communication; Adaptive equalizer; doubly selective channel; iterative receiver; turbo equalization; underwater communication;
  • fLanguage
    English
  • Journal_Title
    Oceanic Engineering, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    0364-9059
  • Type

    jour

  • DOI
    10.1109/JOE.2011.2158013
  • Filename
    5981405