一种改进的卷积LDPC码置信传播译码算法

Abstract

Abstract:

A novel belief propagation (BP) decoding algorithm for convolutional low-density parity-check codes is proposed. The proposed algorithm raises the efficiency of updating the variable information by applying feedback information at each decoding iteration and employs the weighting factor to reduce the error propagation caused by the cycles in the Tanner graph, thus yielding a faster convergence of the decoding. Simulation results show that an error performance better than that of the existing belief propagation algorithm can be achieved, while the 5/8 decoding delay and the computation complexity are effectively reduced. Compared with the existing BP, the proposed algorithm achieves a gain of 0.16 dB at the BER of 10^-6 with the same number of iterations.

Key words: feedback, iterative method, Convolutional codes, low-density parity-check codes, belief propagation

CLC Number:

TN911.22

LIU Yuan-hua;WANG Xin-mei;HU Shu-kai;CHEN Ru-wei. Improved belief propagation algorithm for decoding of convolutional LDPC codes[J].J4, 2009, 36(3): 424-447.

References

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Improved belief propagation algorithm for decoding of convolutional LDPC codes

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