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

Pages: 68 - 71
Published: Aug 12, 2002
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....
Paper Details
Title
Low-power approach for decoding convolutional codes with adaptive Viterbi algorithm approximations
Published Date
Aug 12, 2002
Journal
Pages
68 - 71
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