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Research on the Viterbi and BCJR decoding schemes of convolutional codes under different sources

Dongfeng Yuan, Xiao-Hong Shan

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Abstract

The performance of Viterbi and BCJR (Bahl-Cocke-Jelinek-Raviv) algorithms on AWGN channels is investigated with equally/unequally likely distributed data sources and image sources. On the basis of computer simulations and analysis by comparison, the feasibility of applying the BCJR algorithm to convolutional codes is further explored in this paper.

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What this paper is about

The performance of Viterbi and BCJR (Bahl-Cocke-Jelinek-Raviv) algorithms on AWGN channels is investigated with equally/unequally likely distributed data sources and image sources. On the basis of computer simulations and analysis by comparison, the feasibility of applying the BCJR algorithm to convolutional codes is further explored in this paper.

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The performance of Viterbi and BCJR (Bahl-Cocke-Jelinek-Raviv) algorithms on AWGN channels is investigated with equally/unequally likely distributed data sources and image sources. On the basis of computer simulations and analysis by comparison, the feasibility of applying the BCJR algorithm to convolutional codes is further explored in this paper.

Key concepts: Convolutional code, BCJR algorithm, Soft output Viterbi algorithm, Viterbi algorithm, Turbo code, Computer science, Viterbi decoder, Iterative Viterbi decoding

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