cogcom 18: e1

Research Article

Joint Encoding and Decoding Optimization of LT Codes over Noise Channels

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  • @ARTICLE{10.4108/eai.14-1-2019.161365,
        author={Mingli  Chi and Wenzhu  Sun},
        title={Joint Encoding and Decoding Optimization of LT Codes over Noise Channels},
        journal={EAI Endorsed Transactions on Cognitive Communications: Online First},
        volume={},
        number={},
        publisher={EAI},
        journal_a={COGCOM},
        year={2019},
        month={11},
        keywords={LT Codes, RVN, Belief Propagation, CRC, Error Floor},
        doi={10.4108/eai.14-1-2019.161365}
    }
    
  • Mingli Chi
    Wenzhu Sun
    Year: 2019
    Joint Encoding and Decoding Optimization of LT Codes over Noise Channels
    COGCOM
    EAI
    DOI: 10.4108/eai.14-1-2019.161365
Mingli Chi1,*, Wenzhu Sun1
  • 1: College of computer science and technology, Shandong University of Technology, 255000 Zibo, China
*Contact email: sdutswz@sina.com

Abstract

The low-degree variable nodes and high residual errors of Belief Propagation (BP) decoding are key factors of high error floor of LT Codes over noise channels. A joint encoding and decoding scheme are proposed to lower this error floor. The Regularized Variable-Node (RVN) encoding method is adopted to maximize the minimum degree and avoid the lowdegree variable node. By investigating the characteristic of error patterns in error frames and the relationship between error bits and their Log-likelihood Ratio (LLR) values, the most unreliable bits are identified after BP decoding. Thanks to the Cyclic Redundancy Check (CRC) detector, the residual error bits of BP decoder are identified and corrected by bit flip. The simulation results demonstrate that the proposed method can dramatically reduce the frame error rate in the error floor region at the cost of almost negligible extra computation.