Interleaver optimization by population based metaheuristics

Turbo coding is an influential method of channel coding in telecommunications. The introduction of the turbo principle allowed close approach to the Shannon limit, a theoretical boundary describing the maximum capacity of a noisy communication channel. The invention of the turbo codes and its superior performance in practical applications also initiated a renaissance of channel coding research. The exceptional performance of the turbo codes can be further improved by finding right settings for a particular system. Among others, the structure of the interleaver performing a permutation of input bits is one important property of any turbo code system. In this paper, we present genetic algorithms and differential evolution as two promising optimization methods to find a well-performing turbo code interleaver.