Title :
New schedules for information processing in turbo decoding
Author :
Meshkat, Peyman ; Villasenor, John D.
Author_Institution :
Dept. of Electr. Eng., California Univ., Los Angeles, CA, USA
Abstract :
The framework of Bayesian networks has been used to introduce new ways for decoding parallel concatenated convolutional (turbo) codes. Simulation results show that a noisy received block which does not converge using traditional turbo decoding can converge to the correct value with one or more of the methods introduced here
Keywords :
belief networks; concatenated codes; convergence; convolutional codes; decoding; scheduling; turbo codes; Bayesian networks; convergence; information processing; noisy received block; parallel concatenated convolutional codes; schedules; turbo decoding; Bayesian methods; Belief propagation; Concatenated codes; Convolutional codes; Information processing; Intelligent networks; Iterative decoding; Scheduling algorithm; Timing; Turbo codes;
Conference_Titel :
Information Theory, 1998. Proceedings. 1998 IEEE International Symposium on
Conference_Location :
Cambridge, MA
Print_ISBN :
0-7803-5000-6
DOI :
10.1109/ISIT.1998.708707
