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Nouveau décodeur à complexité réduite pour codes convolutifs de rendement 1/2
| Content Provider | Semantic Scholar |
|---|---|
| Author | Dany, J.-C. Antoine, Jacques Husson, Lionel Paul, Neill Wautier, Armelle Brouet, Jérôme |
| Copyright Year | 2003 |
| Abstract | It is well known that convolutional codes can be optimally decoded by the Viterbi Algorithm (VA). We propose a soft decoding technique where the VA is applied to identify the error vector rather than the information message. In this paper, we show that, with this type of decoding, the exhaustive computation of a vast majority of ACS (Add Compare Select) is unnecessary. Hence, performance close to optimum is achievable with a reduction of complexity. The gain in complexity of the proposed scheme is all the more important as the SNR is high. For instance, for SNR greater than 3 dB, more than 88% of computations for ACS can be avoided when transmitting BPSK symbols on a gaussian channel. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://documents.irevues.inist.fr/bitstream/handle/2042/13780/A51.pdf?sequence=1 |
| Alternate Webpage(s) | http://www.supelec.fr/ecole/radio/Decodeur_complexite_reduite_GRETSI03.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
