Decoding Algorithm

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Tovohery Randrianarisoa - One of the best experts on this subject based on the ideXlab platform.

  • A Decoding Algorithm for Rank Metric Codes.
    arXiv: Information Theory, 2017
    Co-Authors: Tovohery Randrianarisoa
    Abstract:

    In this work we will present Algorithms for Decoding rank metric codes. First we will look at a new Decoding Algorithm for Gabidulin codes using the property of Dickson matrices corresponding to linearized polynomials. We will be using a Berlekamp-Massey-like Algorithm in the process. We will show the difference between our and existing Algorithms. Apart from being a new Algorithm, it is also interesting that it can be modified to get a Decoding Algorithm for general twisted Gabidulin codes.

  • A Decoding Algorithm for Twisted Gabidulin codes
    arXiv: Information Theory, 2017
    Co-Authors: Tovohery Randrianarisoa, Joachim Rosenthal
    Abstract:

    In this work, we modify the Decoding Algorithm for subspace codes by Koetter and Kschischang to get a Decoding Algorithm for (generalized) twisted Gabidulin codes. The Decoding Algorithm we present applies to cases where the code is linear over the base field $\mathbb{F}_q$ but not linear over $\mathbb{F}_{q^n}$.

  • ISIT - A Decoding Algorithm for twisted Gabidulin codes
    2017 IEEE International Symposium on Information Theory (ISIT), 2017
    Co-Authors: Joachim Rosenthal, Tovohery Randrianarisoa
    Abstract:

    In this work, we modify the Decoding Algorithm for subspace codes by Kotter and Kschischang to get a Decoding Algorithm for (generalized) twisted Gabidulin codes. The Decoding Algorithm we present applies to cases where the code is linear over the base field F q but not linear over F q n.

Shigeichi Hirasawa - One of the best experts on this subject based on the ideXlab platform.

  • A Method for Grouping Symbol Nodes of Group Shuffled BP Decoding Algorithm
    IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, 2008
    Co-Authors: Yoshiyuki Sato, Hideki Yagi, Gou Hosoya, Shigeichi Hirasawa
    Abstract:

    In this paper, we propose a method for enhancing performance of a sequential version of the belief-propagation (BP) Decoding Algorithm, the group shuffled BP Decoding Algorithm for low-density parity-check (LDPC) codes. An improved BP Decoding Algorithm, called the shuffled BP Decoding Algorithm, decodes each symbol node in serial at each iteration. To reduce the Decoding delay of the shuffled BP Decoding Algorithm, the group shuffled BP Decoding Algorithm divides all symbol nodes into several groups. In contrast to the original group shuffled BP, which automatically generates groups according to symbol positions, in this paper we propose a method for grouping symbol nodes which generates groups according to the structure of a Tanner graph of the codes. The proposed method can accelerate the convergence of the group shuffled BP Algorithm and obtain a lower error rate in a small number of iterations. We show by simulation results that the Decoding performance of the proposed method is improved compared with those of the shuffled BP Decoding Algorithm and the group shuffled BP Decoding Algorithm.

  • Ecient Reliability-based Soft Decision Decoding Algorithm over Markov Modulated Channel
    2004
    Co-Authors: Hideki Yagi, Toshiyasu Matsushima, Shigeichi Hirasawa
    Abstract:

    We discuss soft-decision Decoding which achieves nearmaximum likelihood Decoding (MLD) of binary block codes over a Markov modulated channel. In this paper, a new soft-decision Decoding Algorithm using a generalized Expectation Maximization (EM) Algorithm is proposed. Each iteration step of the proposed Decoding Algorithm can be regarded as performing MLD over an additive white Gaussian noise (AWGN) channel, so the proposed Decoding Algorithm can employ most of conventional ecient methods devised for the AWGN channel. The simulation results show that the proposed Decoding Algorithm achieves almost the same performance as that of MLD which needs exhaustive search of codewords.

  • an efficient maximum likelihood Decoding Algorithm for linear block codes with algebraic decoder
    IEEE Transactions on Information Theory, 1994
    Co-Authors: T Kaneko, T Nishijima, H Inazumi, Shigeichi Hirasawa
    Abstract:

    A new soft Decoding Algorithm for linear block codes is proposed. The Decoding Algorithm works with any algebraic decoder and its performance is strictly the same as that of maximum-likelihood-Decoding (MLD). Since our Decoding Algorithm generates sets of different candidate codewords corresponding to the received sequence, its Decoding complexity depends on the received sequence. We compare our Decoding Algorithm with Chase (1972) Algorithm 2 and the Tanaka-Kakigahara (1983) Algorithm in which a similar method for generating candidate codewords is used. Computer simulation results indicate, for some signal-to-noise ratios (SNR), that our Decoding Algorithm requires less average complexity than those of the other two Algorithms, but the performance of ours is always superior to those of the other two. >

Joachim Rosenthal - One of the best experts on this subject based on the ideXlab platform.

  • A Decoding Algorithm for Twisted Gabidulin codes
    arXiv: Information Theory, 2017
    Co-Authors: Tovohery Randrianarisoa, Joachim Rosenthal
    Abstract:

    In this work, we modify the Decoding Algorithm for subspace codes by Koetter and Kschischang to get a Decoding Algorithm for (generalized) twisted Gabidulin codes. The Decoding Algorithm we present applies to cases where the code is linear over the base field $\mathbb{F}_q$ but not linear over $\mathbb{F}_{q^n}$.

  • ISIT - A Decoding Algorithm for twisted Gabidulin codes
    2017 IEEE International Symposium on Information Theory (ISIT), 2017
    Co-Authors: Joachim Rosenthal, Tovohery Randrianarisoa
    Abstract:

    In this work, we modify the Decoding Algorithm for subspace codes by Kotter and Kschischang to get a Decoding Algorithm for (generalized) twisted Gabidulin codes. The Decoding Algorithm we present applies to cases where the code is linear over the base field F q but not linear over F q n.

Zhang Tian-yu - One of the best experts on this subject based on the ideXlab platform.

  • Research on the Modified Minimum-Sum Decoding Algorithm of LDPC Codes in MIMO-OFDM System
    Journal of Yunnan University of Nationalities, 2011
    Co-Authors: Zhang Tian-yu
    Abstract:

    BP Decoding Algorithm is usually used to realize the Decoding of LDPC codes,but the hardware circuit of BP Decoding Algorithm is complicated.Minimum-sum Decoding Algorithm can simplify BP Decoding Algorithm,but it is achieved by sacrificing performance.According to the performance defects of minimum-sum Decoding Algorithm,a modified minimum-sum Decoding Algorithm is proposed by using the minimum mean square error rule in order to have a good tradeoff between complexity and Decoding performance.Finally,the proposed Algorithm is applied in MIMO-OFDM system.The simulation results show that,compared with BP Decoding Algorithm and minimum-sum Decoding Algorithm,the modified minimum-sum Decoding Algorithm can decrease Algorithm complexity and keep good Decoding performance.

  • Research on modified TPC Decoding Algorithm
    Journal of Changchun University of Technology, 2010
    Co-Authors: Zhang Tian-yu
    Abstract:

    TPC can obtain lower bit error rate at low SNR close to the Shannon limit.But the hardware circuit of TPC Decoding Algorithm is complicated.Minimum-sum Decoding Algorithm can simplify TPC Decoding Algorithm,but it is achieved by sacrificing Decoding performance.According to likelihood probability,a modified TPC Decoding Algorithm is proposed by introducing offset parameter and normalization parameter simultaneously in order to have a good tradeoff between complexity and Decoding performance.Moreover,the related parameters are calculated by minimum mean square error rule.The simulation results show that,compared with TPC Decoding Algorithm and minimum-sum Decoding Algorithm,the modified TPC Decoding Algorithm can decrease Algorithm complexity and keep good Decoding performance.

  • Research on LDPC Decoding Algorithm based on forgetting coefficient
    Journal of Changchun University of Technology, 2010
    Co-Authors: Zhang Tian-yu
    Abstract:

    The Tanner graph of long LDPC codes usually has no loops and LLR BP Decoding Algorithm is the best soft-decision Decoding Algorithm.The Tanner graph of short LDPC codes usually has loops,so the information within variable nodes isn't mutually independent and the Decoding performance of LLR BP Decoding Algorithm will decrease.According to the characteristics of short LDPC codes,a modified LLR BP Decoding Algorithm is proposed.Parameters of the proposed Algorithm are calculated according to forgetting coefficient.The simulation results show that,compared with LLR BP Decoding Algorithm,Normalized BP Decoding Algorithm and Offset BP Decoding Algorithm,the modified LLR BP Decoding Algorithm can decrease Algorithm complexity and improve LDPC Decoding performance under the condition of loops existing.

  • Research on modified IRA Decoding Algorithm based on minimum mean square error
    Journal of Changchun University of Technology, 2010
    Co-Authors: Zhang Tian-yu
    Abstract:

    BP Decoding Algorithm is usually used to realize Decoding of IRA codes,but the hardware circuit of BP Decoding Algorithm is complicated.Minimum-sum Decoding Algorithm can simplify BP Decoding Algorithm,but it is achieved by sacrificing performance.According to minimum mean square error rule,a modified IRA Decoding Algorithm is proposed in order to have a good tradeoff between complexity and Decoding performance.The simulation results show that,compared with BP Decoding Algorithm,the modified IRA Decoding Algorithm can decrease Algorithm complexity and keep good Decoding performance.Compared with minimum-sum Decoding Algorithm,the complexity of the modified IRA Decoding Algorithm is almost unchanged,but the Decoding performance improves significantly.

  • Research on modified TPC Decoding Algorithm based on offset and normalization
    Journal of Changchun University of Technology, 2010
    Co-Authors: Zhang Tian-yu
    Abstract:

    TPC can obtain lower bit error rate at low SNR close to the Shannon limit.But the hardware circuit of TPC Decoding Algorithm is complicated.Minimum-sum Decoding Algorithm can simplify TPC Decoding Algorithm,but it is achieved by sacrificing Decoding performance.According to likelihood probability,the modified TPC Decoding Algorithm based on offset and normalization is proposed by introducing offset parameter and normalization parameter in order to have a good tradeoff between complexity and Decoding performance.The simulation results show that,compared with TPC Decoding Algorithm and minimum-sum Decoding Algorithm,the modified TPC Decoding Algorithm based on offset and normalization can decrease Algorithm complexity and keep good Decoding performance.

M.j. Seo - One of the best experts on this subject based on the ideXlab platform.

  • An efficient soft-decision Reed-Solomon Decoding Algorithm
    IEEE Transactions on Information Theory, 1994
    Co-Authors: D.j. Taipale, M.j. Seo
    Abstract:

    We develop a computationally efficient soft-decision Reed-Solomon (RS) Decoding Algorithm. Our new Algorithm has direct applications to soft-decision Decoding procedures such as the generalized-minimum-distance Decoding Algorithm. Our particular soft-decision Decoding technique is not the innovation of the Algorithm. The innovation is a new errors-and-erasures RS Decoding Algorithm that only works with different sets of erasures where the size of each set of erasures is reduced by one for each iteration (i.e., generalized-minimum-distance Decoding). A result of each iteration is an error-and-erasure locator polynomial (or locator polynomials) that any RS decoder would produce. Since the new soft-decision RS Decoding Algorithm makes no assumptions on the d-1 erasures, the Algorithm is useful for soft-decision Decoding techniques such as generalized-minimum-distance Decoding. >

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