Low-power approach for decoding convolutional codes with adaptive viterbi algorithm approximations

R. Henning; Chaitali Chakrabarti

Low-power approach for decoding convolutional codes with adaptive viterbi algorithm approximations

R. Henning, Chaitali Chakrabarti

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

14 Scopus citations

Abstract

Significant power reduction can be achieved by exploiting real-time variation in system characteristics while decoding convolutional codes. The approach proposed herein adaptively approximates Viterbi decoding by varying truncation length and pruning threshold of the T-algorithm while employing trace-back memory management. Adaptation is performed according to variations in signal-to-noise ratio, code rate, and maximum acceptable bit error rate. Potential energy reduction of 70 to 97.5% compared to Viterbi decoding is demonstrated. Superiority of adaptive T-algorithm decoding compared to fixed T-algorithm decoding is studied. General conclusions about when applications can particularly benefit from this approach are given.

Original language	English (US)
Title of host publication	Proceedings of the International Symposium on Low Power Electronics and Design, Digest of Technical Papers
Pages	68-71
Number of pages	4
State	Published - 2002
Event	Proceedings of the 2002 International Symposium on Low Power Electronics and Design - Monterey, CA, United States Duration: Aug 12 2002 → Aug 14 2002

Other

Other	Proceedings of the 2002 International Symposium on Low Power Electronics and Design
Country/Territory	United States
City	Monterey, CA
Period	8/12/02 → 8/14/02

Keywords

Adaptive T-algorithm decoding
Convolutional codes
Low power
Viterbi algorithm

ASJC Scopus subject areas

General Engineering

Cite this

Henning, R & Chakrabarti, C 2002, Low-power approach for decoding convolutional codes with adaptive viterbi algorithm approximations. in Proceedings of the International Symposium on Low Power Electronics and Design, Digest of Technical Papers. pp. 68-71, Proceedings of the 2002 International Symposium on Low Power Electronics and Design, Monterey, CA, United States, 8/12/02.

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AB - Significant power reduction can be achieved by exploiting real-time variation in system characteristics while decoding convolutional codes. The approach proposed herein adaptively approximates Viterbi decoding by varying truncation length and pruning threshold of the T-algorithm while employing trace-back memory management. Adaptation is performed according to variations in signal-to-noise ratio, code rate, and maximum acceptable bit error rate. Potential energy reduction of 70 to 97.5% compared to Viterbi decoding is demonstrated. Superiority of adaptive T-algorithm decoding compared to fixed T-algorithm decoding is studied. General conclusions about when applications can particularly benefit from this approach are given.

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BT - Proceedings of the International Symposium on Low Power Electronics and Design, Digest of Technical Papers

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ER -

Low-power approach for decoding convolutional codes with adaptive viterbi algorithm approximations

Abstract

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Keywords

ASJC Scopus subject areas

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