Interleaver Optimization using Population-Based Metaheuristics

0350889 - ÚI 2011 RIV CZ eng J - Journal Article
Snášel, V. - Platoš, J. - Krömer, P. - Abraham, A. - Ouddane, N. - Húsek, Dušan
Interleaver Optimization using Population-Based Metaheuristics.
Neural Network World. Roč. 20, č. 5 (2010), s. 591-608. ISSN 1210-0552
R&D Projects: GA ČR GA205/09/1079
Grant - others:GA ČR(CZ) GA102/09/1494
Institutional research plan: CEZ:AV0Z10300504
Keywords : turbo codes * global optimization * genetic algorithms * differential evolution * noisy communication channel
Subject RIV: IN - Informatics, Computer Science
Impact factor: 0.511, year: 2010

Since their appearance in 1993, first approaching the Shannon limit, turbo codes have given a new direction in the channel encoding field, especially since they have been adopted for multiple norms of telecommunications such as deeper communication. A robust interleaver can significantly contribute to the overall performance a turbo code system. Search for a good interleaver is a complex combinatorial optimization problem. In this paper, we present genetic algorithms and differential evolution, two bio-inspired approaches that have proven the ability to solve non-trivial combinatorial optimization tasks, as promising optimization methods to find a well-performing interleaver for large frame sizes.
Permanent Link: http://hdl.handle.net/11104/0006150