A Recursive Maximum Likelihood Decoding Algorithm for Some Transitive Invariant Binary Block Codes

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概要

• 論文の詳細を見る

• Recently, a trellis-based recursive maximum likelihood decoding (RMLD) algorithm has been proposed for decoding binary linear block codes [1]. This RMLD algorithm is computationally more efficient than the Viterbi decoding algorithm. However, the computational complexity of the RMLD algorithm depends of the sectionalization of a code trellis. In general, minimization of the computational complexity results in non-uniform sectionalization of a code trellis. From implementation point of view, uniform sectionalization of a code trellis and regularity among the trellis sections are desirable. In this paper, we apply the RMLD algorithm to a class of codes which are transitive invariant. This class includes Reed-Muller (RM) codes, the extended and permuted BCH (EBCH) codes and their subcodes. For this class of codes, the binary uniform sectionalization of a code trellis results in the following regular structure. At each step of decoding recursion, the metric table construction procedure is applied uniformly to all the sections and the size and structure of each metric table are the same. This simplifies the implementation of the RMLD algorithm. Furthermore, for all RM codes of lengths 64 and 128 and EBCH codes of lengths 64 and 128 with relatively low rate, the computational complexity of the RMLD algorithm based on the bainary uniform sectionalization of a code trellis is almost the same as that based on an optimum sectionalization of a code trellis.

• 社団法人電子情報通信学会の論文
• 1998-09-25

著者

• FUJIWARA Toru

  Department of Applied Biological Chemistry, The University of Tokyo

• YAMAMOTO Hiroshi

  Department of Macromolecular Science, Graduate School of Science, Osaka University

• Lin Shu

  Department of Horticulture, National Taiwan University

• Kasami Tadao

  Faculty of Graduate School of Information Science, Nara Institute of Science and Technology

• Lin Shu

  California Univ. Ca Usa

• Lin Shu

  The Author Is With The Department Of Electrical And Computer Engineering University Of California

• Lin Shu

  Department Of Electrical Engineering University Of Hawaii At Manoa

• Lin Shu

  Department Of Electrical And Computer Engineering University Of California

• Shu Lin

  University Of Hawaii At Manoa Dept.electrical Engineering Usa.

• TOKUSHIGE Hitoshi

  Graduate School of Information Science, Nara Institute of Science and Technology

• KOUMOTO Takuya

  Graduate School of Information Science, Nara Institute of Science and Technology

• Tokushige H

  Hiroshima City Univ. Hiroshima‐shi Japan

• Tokushige Hitoshi

  Graduate School Of Information Science Nara Institute Of Science And Technology

• Kasami Tadao

  Faculty Of Graduate School Of Information Science Nara Institute Of Science And Technology

• Koumoto Takuya

  Okayama University

• Fujiwara Toru

  Department Of Applied Biological Chemistry Graduate School Of Agricultural And Life Sciences The Uni

• Fujiwara Toru

  Faculty Of Engineering Science Osaka University

• Lin Shu

  University Of Hawaii At Manoa Dept. Electrical Engineering

• Fujiwara T

  Department Of Multimedia Engineering Graduate School Of Information Science And Technology Osaka Uni

• Yamamoto Hiroshi

  Department Of Energy Engineering And Science Nagoya University

• Koumoto T

  Hiroshima City Univ. Hiroshima Jpn

• Lin Shu

  Department Of Chemical Engineering Hwa Hsia College Of Technology And Commerce

• Yamamoto H

  Toyohashi Univ. Technol. Toyohashi‐shi Jpn

• Yamamoto Hiroshi

  Departmemt Of Chemical Engineering University Of Tokyo

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