Title :
List decoding of turbo codes
Author :
Narayanan, Krishna R. ; Stüber, Gordon L.
Author_Institution :
Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
List decoding of turbo codes is analyzed under the assumption of a maximum-likelihood (ML) list decoder. It is shown that large asymptotic gains can be achieved on both the additive white Gaussian noise (AWGN) and fully-interleaved flat Rayleigh fading channels. It is also shown that the relative asymptotic gains for turbo codes are larger than those for convolutional codes. Finally, a practical list decoding algorithm based on the list output Viterbi algorithm (LOVA) is proposed as an approximation to the ML list decoder. Simulation results show that the proposed algorithm provides significant gains corroborating the analytical results. The asymptotic gain manifests itself as a reduction in the bit error rate (BER) and frame error rate (FER) floor of turbo codes
Keywords :
Gaussian channels; Rayleigh channels; Viterbi decoding; concatenated codes; convolutional codes; maximum likelihood decoding; AWGN channels; BER reduction; FER reduction; additive white Gaussian noise channels; asymptotic gains; bit error rate; frame error rate; fully-interleaved flat Rayleigh fading channels; list decoding; list output Viterbi algorithm; maximum-likelihood list decoder; simulation results; turbo codes; AWGN; Additive white noise; Analytical models; Approximation algorithms; Bit error rate; Convolutional codes; Fading; Maximum likelihood decoding; Turbo codes; Viterbi algorithm;
Conference_Titel :
Communications, 1998. ICC 98. Conference Record. 1998 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-4788-9
DOI :
10.1109/ICC.1998.682604
