Title :
Braided Convolutional Codes: A New Class of Turbo-Like Codes
Author :
Zhang, Wei ; Lentmaier, Michael ; Zigangirov, Kamil Sh ; Costello, Daniel J., Jr.
Author_Institution :
Dept. of Electr. Eng., Univ. of Notre Dame, Notre Dame, IN, USA
Abstract :
We present a new class of iteratively decodable turbo-like codes, called braided convolutional codes. Constructions and encoding procedures for tightly and sparsely braided convolutional codes are introduced. Sparsely braided codes exhibit good convergence behavior with iterative decoding, and a statistical analysis using Markov permutors shows that the free distance of these codes grows linearly with constraint length, i.e., they are asymptotically good.
Keywords :
Markov processes; convolutional codes; iterative methods; turbo codes; Markov permutors; braided convolutional codes; iterative decoding; iteratively decodable turbo-like codes; sparsely braided codes; statistical analysis; Block codes; Convergence; Convolutional codes; Data communication; Encoding; Iterative decoding; Parity check codes; Pipelines; Product codes; Statistical analysis; Braided convolutional codes; codes on graphs; convolutional permutor; free distance; iterative decoding; turbo- like codes;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2009.2034784