Title :
Neural network decoding of turbo codes
Author :
Annauth, R. ; Rughooputh, Harry C S
Author_Institution :
Fac. of Eng., Univ. of Mauritius, Mauritius
Abstract :
Berrou et al. (1993) presented a new class of codes (turbo codes) whose performances in terms of bit error rate (BER) are very close to Shannon´s limit. Very low BER of 10-5 at Eb/No ratio of 0.7 dB has been achieved using iterative decoding of turbo codes. However, the decoding scheme is characterized by complex receiver structures, high computational costs, and long iterative procedures. In this paper, we describe a neural network decoder for turbo codes. Simulation results reveal that this novel decoder has a performance very close to the maximum a posteriori decoder
Keywords :
error correction codes; iterative decoding; neural nets; turbo codes; Shannon limit; bit error rate; iterative decoding; neural network; turbo codes; AWGN; Additive white noise; Bit error rate; Error correction codes; Feeds; Iterative algorithms; Iterative decoding; Neural networks; Switches; Turbo codes;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.836196