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2012•Applied Mechanics and MaterialsOpen access

Realization of the Viterbi Algorithm in MLSE with Intersymbol Interference

Ying Lu, Quan Xu, Zhi Gang Liu

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Abstract

Optimum receiver model for channels with Intersymbol Interference (ISI) and Additive White Gaussian Noise (AWGN) are introduced to deduce the Viterbi algorithm in the Maximum-Likelihood Sequence Estimation (MLSE). Finally, we use Matlab to simulate the algorithm in three different channels and analyze the experiment results. Analyses show that the Viterbi algorithm is applicable for any channel which is optimum from a probability of error viewpoint; the MLSE for channels with ISI has a computational complexity that grows exponentially with the length of channels time dispersion L; the loss of performance is negligible when the decoding delay achieves 5L.

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What this paper is about

Optimum receiver model for channels with Intersymbol Interference (ISI) and Additive White Gaussian Noise (AWGN) are introduced to deduce the Viterbi algorithm in the Maximum-Likelihood Sequence Estimation (MLSE). Finally, we use Matlab to simulate the algorithm in three different channels and analyze the experiment results. Analyses show that the Viterbi algorithm is applicable for any channel which is optimum from a probability of error viewpoint; the MLSE for channels with ISI has a computational complexity that grows exponentially with the length of channels time dispersion L; the loss of performance is negligible when the decoding delay achieves 5L.

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Available abstract

Optimum receiver model for channels with Intersymbol Interference (ISI) and Additive White Gaussian Noise (AWGN) are introduced to deduce the Viterbi algorithm in the Maximum-Likelihood Sequence Estimation (MLSE). Finally, we use Matlab to simulate the algorithm in three different channels and analyze the experiment results. Analyses show that the Viterbi algorithm is applicable for any channel which is optimum from a probability of error viewpoint; the MLSE for channels with ISI has a computational complexity that grows exponentially with the length of channels time dispersion L; the loss of performance is negligible when the decoding delay achieves 5L.

Key concepts: Intersymbol interference, Viterbi algorithm, Maximum likelihood sequence estimation, Algorithm, Additive white Gaussian noise, Computer science, Soft output Viterbi algorithm, Nyquist ISI criterion

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