Persistent Link:
http://hdl.handle.net/10150/609390
Title:
Maximum Likelihood Decoding Scheme for Convolutional Codes
Author:
Ng, Wai-Hung; Kim, Frank M. H.; Tashiro, Satoru
Affiliation:
The Boeing Aerospace Company
Issue Date:
1976-09
Rights:
Copyright © International Foundation for Telemetering
Collection Information:
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.
Publisher:
International Foundation for Telemetering
Journal:
International Telemetering Conference Proceedings
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.
Sponsors:
International Foundation for Telemetering
ISSN:
0884-5123; 0074-9079
Additional Links:
http://www.telemetry.org/

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.titleMaximum Likelihood Decoding Scheme for Convolutional Codesen_US
dc.contributor.authorNg, Wai-Hungen
dc.contributor.authorKim, Frank M. H.en
dc.contributor.authorTashiro, Satoruen
dc.contributor.departmentThe Boeing Aerospace Companyen
dc.date.issued1976-09en
dc.rightsCopyright © International Foundation for Telemeteringen
dc.description.collectioninformationProceedings 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
dc.publisherInternational Foundation for Telemeteringen
dc.description.abstractIn 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.en
dc.description.sponsorshipInternational Foundation for Telemeteringen
dc.identifier.issn0884-5123en
dc.identifier.issn0074-9079en
dc.identifier.urihttp://hdl.handle.net/10150/609390en
dc.identifier.journalInternational Telemetering Conference Proceedingsen
dc.typetexten
dc.typeProceedingsen
dc.relation.urlhttp://www.telemetry.org/en
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.