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R. Sujan, et al., “Adaptive ‘Soft’ Sliding Block Decoding of Convolutional Code Using the Artificial Neural Net-Work,” Transactions on Emerging Telecommunications Technologies, 2012.

has been cited by the following article:

• TITLE: Majority Voting Procedure Allowing Soft Decision Decoding of Linear Block Codes on Binary Channels

  AUTHORS: Saïd Nouh, Achraf El Khatabi, Mostafa Belkasmi

  KEYWORDS: Error Correcting Codes; Genetic Algorithms; HIHO Decoder; SIHO Decoder; Vote Procedure

  JOURNAL NAME: International Journal of Communications, Network and System Sciences, Vol.5 No.9, September 18, 2012

  ABSTRACT: In this paper we present an efficient algorithm to decode linear block codes on binary channels. The main idea consists in using a vote procedure in order to elaborate artificial reliabilities of the binary received word and to present the obtained real vector r as inputs of a SIHO decoder (Soft In/Hard Out). The goal of the latter is to try to find the closest codeword to r in terms of the Euclidean distance. A comparison of the proposed algorithm over the AWGN channel with the Majority logic decoder, Berlekamp-Massey, Bit Flipping, Hartman-Rudolf algorithms and others show that it is more efficient in terms of performance. The complexity of the proposed decoder depends on the weight of the error to decode, on the code structure and also on the used SIHO decoder.