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This paper is aimed at the problem of designing optimized interleavers for parallel concatenated convolutional codes (PCCC) that satisfy several requirements simultaneously: 1) designing interleavers tailored to the constituent codes of the PCCC; 2) improving the distance spectra of the resulting turbo codes which dominate their asymptotic performance; and 3) constructing optimized interleavers recursively so that they are implicitly prunable. Two more modifications of a previously developed iterative interleaver growth algorithm (IGA) of polynomial complexity [F. Daneshragan et al., Sept. 1999] are presented to improve the performance of the optimized interleavers at a reduced complexity: 1) a growing window is used to trap error patterns of proper length in order to form the cost function; and 2) we employ error feedback to further improve the distance spectrum, of the optimized codes and to reduce complexity. The optimization is achieved via constrained minimization of a cost function closely related to the asymptotic bit error rate (BER) or frame error rate (FER) of the codes.
Communications, 2003. ICC '03. IEEE International Conference on (Volume:5 )
Date of Conference: 11-15 May 2003