SOVA decoding in symmetric alpha-stable noise
Soft-Output Viterbi Algorithm (SOVA) is one type of recovery memory-less Markov Chain and is used widely to decode convolutional codes. Fundamentally, conventional SOVA is designed on the basis of Maximum A-Posteriori Probability (APP) with the assumption of normal distribution. Therefore, conventio...
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| Language: | en |
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2011
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| Online Access: | http://eprints.sunway.edu.my/111/1/ICS2011_15.pdf http://eprints.sunway.edu.my/111/ |
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| _version_ | 1831341264501473280 |
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| author | Pu, Chuan Hsian |
| author_facet | Pu, Chuan Hsian |
| author_sort | Pu, Chuan Hsian |
| building | Sunway Campus Library |
| collection | Institutional Repository |
| content_provider | Sunway University |
| content_source | Sunway Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Soft-Output Viterbi Algorithm (SOVA) is one type of recovery memory-less Markov Chain and is used widely to decode convolutional codes. Fundamentally, conventional SOVA is designed on the basis of Maximum A-Posteriori Probability (APP) with the assumption of normal distribution. Therefore, conventional SOVA fails miserably in the presence of symmetric alpha stable noise S\ensuremathα S which is one form of stable random processes widely accepted for impulsive noise modeling. The author studies and has improved the performance of conventional SOVA by introducing Cauchy function into path-metric calculation. Substantial performance improvement was gained from Mento Carlo Simulation for SOVA based turbo codes. |
| format | Conference or Workshop Item |
| id | my.sunway.eprints.111 |
| institution | Sunway University |
| language | en |
| publishDate | 2011 |
| record_format | eprints |
| spelling | my.sunway.eprints.1112012-10-16T09:20:44Z http://eprints.sunway.edu.my/111/ SOVA decoding in symmetric alpha-stable noise Pu, Chuan Hsian QA Mathematics Soft-Output Viterbi Algorithm (SOVA) is one type of recovery memory-less Markov Chain and is used widely to decode convolutional codes. Fundamentally, conventional SOVA is designed on the basis of Maximum A-Posteriori Probability (APP) with the assumption of normal distribution. Therefore, conventional SOVA fails miserably in the presence of symmetric alpha stable noise S\ensuremathα S which is one form of stable random processes widely accepted for impulsive noise modeling. The author studies and has improved the performance of conventional SOVA by introducing Cauchy function into path-metric calculation. Substantial performance improvement was gained from Mento Carlo Simulation for SOVA based turbo codes. 2011-06 Conference or Workshop Item PeerReviewed text en http://eprints.sunway.edu.my/111/1/ICS2011_15.pdf Pu, Chuan Hsian (2011) SOVA decoding in symmetric alpha-stable noise. In: Symposium on Information & Computer Sciences (1st). |
| spellingShingle | QA Mathematics Pu, Chuan Hsian SOVA decoding in symmetric alpha-stable noise |
| title | SOVA decoding in symmetric alpha-stable noise |
| title_full | SOVA decoding in symmetric alpha-stable noise |
| title_fullStr | SOVA decoding in symmetric alpha-stable noise |
| title_full_unstemmed | SOVA decoding in symmetric alpha-stable noise |
| title_short | SOVA decoding in symmetric alpha-stable noise |
| title_sort | sova decoding in symmetric alpha-stable noise |
| topic | QA Mathematics |
| url | http://eprints.sunway.edu.my/111/1/ICS2011_15.pdf http://eprints.sunway.edu.my/111/ |
| url_provider | http://eprints.sunway.edu.my/ |