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A reduced-state Viterbi algorithm for blind sequence estimation of DPSK sources

Tongtong Li, Zhi Ding

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Abstract

The Viterbi algorithm is the optimum decoding algorithm for convolutional codes and has often served as a standard technique in digital communication systems for maximum likelihood sequence estimation. With the Viterbi algorithm, the computational complexity increases exponentially with the constraint length of the convolutional code. Reducing the constraint length (hence the number of states) would permit major simplification in the implementation of the Viterbi algorithm. In this paper, a reduced-state Viterbi algorithm for blind sequence estimation of DPSK sources is presented. It can reduce number of states in the Viterbi algorithm by at least half. The reduced state DPSK Viterbi decoder can be made much faster without any performance loss.

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What this paper is about

The Viterbi algorithm is the optimum decoding algorithm for convolutional codes and has often served as a standard technique in digital communication systems for maximum likelihood sequence estimation. With the Viterbi algorithm, the computational complexity increases exponentially with the constraint length of the convolutional code. Reducing the constraint length (hence the number of states) would permit major simplification in the implementation of the Viterbi algorithm. In this paper, a reduced-state Viterbi algorithm for blind sequence estimation of DPSK sources is presented. It can reduce number of states in the Viterbi algorithm by at least half. The reduced state DPSK Viterbi decoder can be made much faster without any performance loss.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The Viterbi algorithm is the optimum decoding algorithm for convolutional codes and has often served as a standard technique in digital communication systems for maximum likelihood sequence estimation. With the Viterbi algorithm, the computational complexity increases exponentially with the constraint length of the convolutional code. Reducing the constraint length (hence the number of states) would permit major simplification in the implementation of the Viterbi algorithm. In this paper, a reduced-state Viterbi algorithm for blind sequence estimation of DPSK sources is presented. It can reduce number of states in the Viterbi algorithm by at least half. The reduced state DPSK Viterbi decoder can be made much faster without any performance loss.

Key concepts: Viterbi algorithm, Iterative Viterbi decoding, Soft output Viterbi algorithm, Viterbi decoder, Convolutional code, Forward algorithm, Computer science, Algorithm

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