Maximum Likelihood Decoding Scheme for Convolutional Codes
| dc.contributor.author | Ng, Wai-Hung | |
| dc.contributor.author | Kim, Frank M. H. | |
| dc.contributor.author | Tashiro, Satoru | |
| dc.date.accessioned | 2016-05-14T02:12:21Z | en |
| dc.date.available | 2016-05-14T02:12:21Z | en |
| dc.date.issued | 1976-09 | en |
| dc.identifier.issn | 0884-5123 | en |
| dc.identifier.issn | 0074-9079 | en |
| dc.identifier.uri | http://hdl.handle.net/10150/609390 | en |
| dc.description | International Telemetering Conference Proceedings / September 28-30, 1976 / Hyatt House Hotel, Los Angeles, California | en_US |
| dc.description.abstract | In recent years the application of coding techniques to enhance digital data transmission has become widely accepted. In general, one would assume that a maximum likelihood decoding of convolutional codes would be impractical for long constraint length codes because the general approach of sequential decoding algorithms utilize very few properties of the code and hence require a considerable effort to decode the received data sequence. In this paper, several structure and distance properties of the convolutional codes for different constraint lengths are derived and utilized in developing an efficient maximum likelihood decoding scheme. Under the proposed decoding threshold conditions, which are functions of the distance properties of the utilized codes, the required number of decoding operations can be reduced markedly. The analysis has been supported by computer simulations and by the development and testing of a prototype decoder. Key results are presented and discussed. | |
| dc.description.sponsorship | International Foundation for Telemetering | en |
| dc.language.iso | en_US | en |
| dc.publisher | International Foundation for Telemetering | en |
| dc.relation.url | http://www.telemetry.org/ | en |
| dc.rights | Copyright © International Foundation for Telemetering | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
| dc.title | Maximum Likelihood Decoding Scheme for Convolutional Codes | en_US |
| dc.type | text | en |
| dc.type | Proceedings | en |
| dc.contributor.department | The Boeing Aerospace Company | en |
| dc.identifier.journal | International Telemetering Conference Proceedings | en |
| dc.description.collectioninformation | Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection. | en |
| refterms.dateFOA | 2018-06-17T22:40:49Z | |
| html.description.abstract | In recent years the application of coding techniques to enhance digital data transmission has become widely accepted. In general, one would assume that a maximum likelihood decoding of convolutional codes would be impractical for long constraint length codes because the general approach of sequential decoding algorithms utilize very few properties of the code and hence require a considerable effort to decode the received data sequence. In this paper, several structure and distance properties of the convolutional codes for different constraint lengths are derived and utilized in developing an efficient maximum likelihood decoding scheme. Under the proposed decoding threshold conditions, which are functions of the distance properties of the utilized codes, the required number of decoding operations can be reduced markedly. The analysis has been supported by computer simulations and by the development and testing of a prototype decoder. Key results are presented and discussed. |
