Deficient decoding for convolutional codes
Takeshi Hashimoto, Suguru Arimotos
Abstract
Takeshi Hashimoto, Suguru Arimotos
Abstract
Abstract Tree codes are so important that they often appear in information theory. Highly reliable coding systems may be realized in view of their sequential decoding. While a number of analyses have been made of the probability of error in sequential decoding and of the amount of calculation required for decoding only a few analyses are presently available on the various characteristics when sequential decoding is applied to convolutional codes. Here, we shall evaluate the so‐called deficient decoding that occurs when convolutional codes are sequentially decoded by decoders with finite decoding speeds. The evaluation will be based on the findings of recent studies on the amount of calculation required for the sequential convolutional codes.
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Abstract Tree codes are so important that they often appear in information theory. Highly reliable coding systems may be realized in view of their sequential decoding. While a number of analyses have been made of the probability of error in sequential decoding and of the amount of calculation required for decoding only a few analyses are presently available on the various characteristics when sequential decoding is applied to convolutional codes. Here, we shall evaluate the so‐called deficient decoding that occurs when convolutional codes are sequentially decoded by decoders with finite decoding speeds. The evaluation will be based on the findings of recent studies on the amount of calculation required for the sequential convolutional codes.
Key concepts: Sequential decoding, Convolutional code, Decoding methods, Serial concatenated convolutional codes, List decoding, Computer science, Algorithm, Berlekamp–Welch algorithm