Design of complexity-optimized raptor codes for BI-AWGN channel

This paper aims to design a class of Raptor codes with optimized complexity for the binary input additive white Gaussian noise (BI-AWGN) channel under the joint decoding framework in which soft information is exchanged between the pre-code and the LT code iteratively. Utilizing the belief propagatio...

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Bibliographic Details
Published in:2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) pp. 824 - 829
Main Authors: Chuangmu Yao, Zhaoyang Zhang, Kun Tu
Format: Conference Proceeding
Language:English
Published: IEEE 01.09.2013
Subjects:
Approximation methods
Complexity theory
Decoding
Encoding
Iterative decoding
Optimization
ISSN:2166-9570
Online Access:Get full text
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Summary:This paper aims to design a class of Raptor codes with optimized complexity for the binary input additive white Gaussian noise (BI-AWGN) channel under the joint decoding framework in which soft information is exchanged between the pre-code and the LT code iteratively. Utilizing the belief propagation (BP) decoder, the decoding complexity is measured by the average number of arithmetic operations needed to correctly recover each information bit. Based on the analytical asymptotic convergence analysis which is built upon extrinsic information transfer (EXIT) charts, we develop a numerical approximation for the number of iterations needed for measuring the decoding complexity, and then formulate an optimization problem for the design of efficient output degree distributions. We further discuss the fundamental problem of complexity-rate tradeoff in Raptor code design. Simulations show that the optimized distribution indeed achieves lower complexity without much performance loss compared to other existing rate-optimized Raptor Codes.
ISSN:2166-9570
DOI:10.1109/PIMRC.2013.6666250