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Journal of Computer Applications

Improved Normalized BP-Based decoding algorithm for low density parity check code

Yanping Li

Published Jan 1, 2012• 0 citations
OpenAlex

Abstract

To further improve the decoding performance of the Normalized BP-Based algorithm,an improved Normalized BP-Based algorithm was proposed.The correction factor was changed dynamically according the amount of the information from the check nodes to variable nodes in order to achieve non-linear compensation of BP-Based algorithm.The simulation results show that when the bit error rate was less than 0.5×10-2,the improved algorithms could get about 0.1 dB gain,compared with Normalized BP-Based algorithm,only with slight increase in complexity,and the number of iterations did not increase.

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To solve the problem of high average running time,an improved decoding algorithm was proposed which was combined by BP algorithm and WBF algorithm.The parity check was added in each BP iterative decoding,and flipping criterions which were passed from check nodes to information nodes were weighted by the reliable information of received sequence.Then a bit flipping measure was to be taken according to specific rules in order to obtain correct codes,and a parity check was added again.Simulation results on Additive White Gaussian Noise(AWGN) channel show that,the improved algorithm can decrease the average running time effectively for LDPC codes while maintaining the excellent decoding performance as BP algorithm.And compared with classical BP algorithm,the effect of the different maximum numbers of iterations,different lengths of codes and different code rates for the improved decoding algorithm are analyzed.
A BP-based algorithm with 2-dimensional classified normalized correction is developed to reduce the complexity and improve the performance of decoding algorithm for the low density parity check (LDPC) codes. The algorithm first utilizes classification according to the absolute values of incoming messages in check nodes. Then it uses 2-dimensional normalization to correct the minimum and sub-minimum values. The 2-dimensional normalized factors can be calculated respectively by using probability and statistic theory in the initialization step. Simulation results illustrate that the proposed algorithm achieves better performance in bit error ratio (BER) and average iteration number than normalized BP-based algorithm in the high signal noise ratio (SNR) region, i.e., it can achieve 0.4 dB SNR gain and reduce 20% number of iterations at BER= 5 10  , whose complexity is also much less than that of belief propagation (BP) algorithm. It is concluded that the proposed algorithm offers better tradeoff between performance and complexity.  Index Terms—channel coding theory, density evolution, Iterative decoding algorithm
In order to reduce the performance loss of UMP BP-based decoding algorithm relative to LLR-BP decoding algorithm,an improved UMP BP-based decoding algorithm is proposed.When the check nodes process the message,the normalized BP-based decoding algorithm and offset BP-based decoding algorithm are integrated effectively by setting a correction factor and an offset factor reasonably.When the variable nodes process the message,an oscillation compensation algorithm based on LLR-BP decoding algorithm is introduced.Simulation results show that based on the irregular LDPC codes and under the condition of the same bit error rate within a certain range,the improved UMP BP-based decoding algorithm improves the decoding performance greatly compared with the three decoding algorithms which are based on UMP BP,normalized BP and offset BP decoding algorithms,respectively,and therefore quite efficiently approaches to the LLR-BP decoding algorithm which has excellent performance.
An improved decoding algorithm based on minimum mean square error(MMSE) for low-density parity-check(LDPC) codes is proposed.The new algorithm combines processing methods of two modified uniformly most powerful(UMP) BP-based algorithms(normalized UMP BP-based algorithm and offset UMP BP-based algorithm) and attains the corresponding normalization factor and offset factor according to MMSE criterion.Simulations indicate that,compared with the two above-mentioned algorithms,a gain of 0.03 dB can be achieved at bit error rate(BER) of 10-6 with the proposed algorithm when a(3,6) regular LDPC code of code length 1 008 and code rate 1/2 is used.
A novel Low-Density Parity-Check(LDPC) decoding algorithm was proposed,which integrates the serial belief propagation mechanism with the normalized BP-Based updating rule.The algorithm propagates the belief according to certain order of the check nodes,thus improves the convergence property of the belief propagation.Meanwhile,the algorithm efficiently lowers the decoding complexity by using the normalized BP-Based updating rule,which makes the algorithm to adapt to the implementation of hardware.Simulation was performed under the AWGN channel and results show that,compared with prior LDPC decoding algorithm,the proposed algorithm is able to accelerate the convergence speed of decoding obviously and enhance the decoding performance significantly.