Constructing error-correcting codes with huge distances

Summary, in English

The class of error-correcting convolutional codes is commonly used for reliable data transmission in mobile, satellite, and space-communication. Demanding simultaneously larger capacities and smaller error probabilities, convolutional codes with large free distances are needed. Such convolutional codes are in general characterized by large overall constraint lengths, increasing the complexity of determining the corresponding code properties, such as the free distance.



The BEAST – Bidirectional Effcient Algorithm for Searching Trees – will be presented as an alternative, less complex, approach to determine the free distance of convolutional codes. As an example a rate R = 5/20 hypergraph-based woven convolutional code with overall constraint length 67 and constituent convolutional codes is presented. Even though using BEAST, determining the free distance of such a convolutional code is a challenge. Using parallel processing and a common huge storage, it was possible to determine the this convolutional code has free distance 120, which is remarkably large.

• Author: Florian Hug
• Department/s: Department of Electrical and Information Technology
• Publishing year: 2009
• Language: English
• Document type: Conference paper
• Topic: Electrical Engineering, Electronic Engineering, Information Engineering
• Conference name: Partnership for Advanced Computing in Europe (PRACE) code porting workshop (invited talk)
• Conference date: 2009-10-13 - 2009-10-14
• Status: Published
• Research group: Information Theory