IEEE Transactions on Information Theory
Fundamentals of Convolutional Coding
Fundamentals of Convolutional Coding
Error Control Coding, Second Edition
Error Control Coding, Second Edition
Time-varying periodic convolutional codes with low-density parity-check matrix
IEEE Transactions on Information Theory
Code construction and decoding of parallel concatenated tail-biting codes
IEEE Transactions on Information Theory
A note on tailbiting codes and their feedback encoders
IEEE Transactions on Information Theory
Turbo decoding as an instance of Pearl's “belief propagation” algorithm
IEEE Journal on Selected Areas in Communications
Iterative decoding of compound codes by probability propagation in graphical models
IEEE Journal on Selected Areas in Communications
On the application of BP decoding to convolutional and turbo codes
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
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This paper presents a new approach to decode turbo codes using a nonbinary belief propagation decoder. The proposed approach can be decomposed into two main steps. First, a nonbinary Tanner graph representation of the turbo code is derived by clustering the binary parity-check matrix of the turbo code. Then, a group belief propagation decoder runs several iterations on the obtained nonbinary Tanner graph. We show in particular that it is necessary to add a preprocessing step on the parity-check matrix of the turbo code in order to ensure good topological properties of the Tanner graph and then good iterative decoding performance. Finally, by capitalizing on the diversity which comes from the existence of distinct efficient preprocessings, we propose a new decoding strategy, called decoder diversity, that intends to take benefits from the diversity through collaborative decoding schemes.