• DocumentCode
    1892108
  • Title

    Efficient implementations of the sum-product algorithm for decoding LDPC codes

  • Author

    Hu, Xiao Yu ; Eleftheriou, Evangelos ; Arnold, Dieter Michael ; Dholakia, Ajay

  • Author_Institution
    IBM Zurich Res. Lab., Ruschlikon, Switzerland
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    1036
  • Abstract
    Efficient implementations of the sum-product algorithm (SPA) are presented for decoding low-density parity-check (LDPC) codes using log-likelihood ratios (LLR) as messages between symbol and parity-check nodes. Various reduced-complexity derivatives of the LLR-SPA are proposed. Both serial and parallel implementations are investigated, leading to trellis and tree topologies, respectively. Furthermore, by exploiting the inherent robustness of LLRs, it is shown, via simulations, that coarse quantization tables are sufficient to implement complex core operations with negligible or no loss in performance. The unified treatment of decoding techniques for LDPC codes presented here provides flexibility in selecting the appropriate design point in high-speed applications from a performance, latency and computational complexity perspective
  • Keywords
    binary codes; block codes; computational complexity; iterative decoding; linear codes; quantisation (signal); table lookup; tree codes; trees (mathematics); trellis codes; LDPC codes; binary codes; iterative decoding; linear block code; log-likelihood ratios; low-density parity-check codes; parity-check nodes; quantization tables; reduced-complexity derivatives; sum-product algorithm; symbol nodes; tree topologies; trellis topologies; Computational complexity; Computational modeling; Decoding; Delay; Parity check codes; Performance loss; Quantization; Robustness; Sum product algorithm; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Telecommunications Conference, 2001. GLOBECOM '01. IEEE
  • Conference_Location
    San Antonio, TX
  • Print_ISBN
    0-7803-7206-9
  • Type

    conf

  • DOI
    10.1109/GLOCOM.2001.965575
  • Filename
    965575