1997
DOI: 10.1109/26.649755
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Adaptive Viterbi decoding of convolutional codes over memoryless channels

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Cited by 79 publications
(46 citation statements)
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“…A simple change of the input configuration of the simple GDI cell corresponds to very different Boolean functions [6]. This GDIL undoubtedly reduces area as lesser number of LUTs and CLBs are used in FPGA prototyping [7].…”
Section: Gdil Based Viterbimentioning
confidence: 99%
“…A simple change of the input configuration of the simple GDI cell corresponds to very different Boolean functions [6]. This GDIL undoubtedly reduces area as lesser number of LUTs and CLBs are used in FPGA prototyping [7].…”
Section: Gdil Based Viterbimentioning
confidence: 99%
“…As convolutional codes become more powerful, Power Consumption Ratio Figure 15 Power consumption ratio of phong shading and gouraud shading: one triangle shading the complexity of the corresponding decoders generally increases. The Viterbi algorithm (VA) [16,17], which is the most extensively employed decoding algorithm for convolutional codes, works well for codes with short constraint length K. For more powerful codes with large constraint lengths the Adaptive Viterbi algorithm (AVA) [18,19] is used. It reduces the average number of computations per decoded information bit.…”
Section: Adaptive Viterbi Decodingmentioning
confidence: 99%
“…In Adaptive Viterbi Algorithms (AVA), developed in [7][8][9], the decoding performance is increased by reducing the number of operations required to decode a single bit. This is achieved by reducing truncation length (TL) or by reducing the number of survivor paths¸ i.e., those paths that are kept in order to find the optimum path.…”
Section: Receiver Energy Modelmentioning
confidence: 99%