Dynamics and performance analysis of analog iterative decoding for low-density parity-check (LDPC) codes

2006 ◽  
Vol 54 (1) ◽  
pp. 61-70 ◽  
Author(s):  
S. Hemati ◽  
A.H. Banihashemi
2013 ◽  
Vol 340 ◽  
pp. 471-475
Author(s):  
Fei Zhong ◽  
Shu Xu Guo

To improve upon the Low-Density Parity-Check (LDPC) codes , incorporating compressed sensing (CS) and information redundancy, a new joint decoding algorithm frame is presented. The proposed system exploits the information redundancy by CS reconstruction during the iterative decoding process to correct decoding of LDPC codes. The simulation results show that the algorithm presented can improve system decoding performance and obviously make bit error ratio (BER) lower then traditional LDPC codes. In addition, a relatively short argument is given on different CS reconstructed algorithms in proposed system, the new design is shown to benefit from different CS reconstructed algorithms.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Chakir Aqil ◽  
Ismail Akharraz ◽  
Abdelaziz Ahaitouf

In this study, we propose a “New Reliability Ratio Weighted Bit Flipping” (NRRWBF) algorithm for Low-Density Parity-Check (LDPC) codes. This algorithm improves the “Reliability Ratio Weighted Bit Flipping” (RRWBF) algorithm by modifying the reliability ratio. It surpasses the RRWBF in performance, reaching a 0.6 dB coding gain at a Binary Error Rate (BER) of 10−4 over the Additive White Gaussian Noise (AWGN) channel, and presents a significant reduction in the decoding complexity. Furthermore, we improved NRRWBF using the sum of the syndromes as a criterion to avoid the infinite loop. This will enable the decoder to attain a more efficient and effective decoding performance.


2007 ◽  
Vol 17 (01) ◽  
pp. 103-123 ◽  
Author(s):  
JAMES S. PLANK ◽  
MICHAEL G. THOMASON

As peer-to-peer and widely distributed storage systems proliferate, the need to perform efficient erasure coding, instead of replication, is crucial to performance and efficiency. Low-Density Parity-Check (LDPC) codes have arisen as alternatives to standard erasure codes, such as Reed-Solomon codes, trading off vastly improved decoding performance for inefficiencies in the amount of data that must be acquired to perform decoding. The scores of papers written on LDPC codes typically analyze their collective and asymptotic behavior. Unfortunately, their practical application requires the generation and analysis of individual codes for finite systems. This paper attempts to illuminate the practical considerations of LDPC codes for peer-to-peer and distributed storage systems. The three main types of LDPC codes are detailed, and a huge variety of codes are generated, then analyzed using simulation. This analysis focuses on the performance of individual codes for finite systems, and addresses several important heretofore unanswered questions about employing LDPC codes in real-world systems.


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