scholarly journals Weighted-Bit-Flipping-Based Sequential Scheduling Decoding Algorithms for LDPC Codes

2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Qing Zhu ◽  
Le-nan Wu
Keyword(s):  
Belief Propagation ◽  
Scheduling Algorithm ◽  
Simple Algorithm ◽  
Ldpc Codes ◽  
Satellite Communications ◽  
Low Complexity ◽  
Computation Complexity ◽  
Tanner Graph ◽  
Decoding Algorithms ◽  
Video Broadcasting

Low-density parity-check (LDPC) codes can be applied in a lot of different scenarios such as video broadcasting and satellite communications. LDPC codes are commonly decoded by an iterative algorithm called belief propagation (BP) over the corresponding Tanner graph. The original BP updates all the variable-nodes simultaneously, followed by all the check-nodes simultaneously as well. We propose a sequential scheduling algorithm based on weighted bit-flipping (WBF) algorithm for the sake of improving the convergence speed. Notoriously, WBF is a low-complexity and simple algorithm. We combine it with BP to obtain advantages of these two algorithms. Flipping function used in WBF is borrowed to determine the priority of scheduling. Simulation results show that it can provide a good tradeoff between FER performance and computation complexity for short-length LDPC codes.

A Min-Sum Algorithm Suitable for Hardware Implementation Based on LDPC Codes

2011 ◽  
Vol 271-273 ◽  
pp. 458-463
Author(s):  
Rui Ping Chen ◽  
Zhong Xun Wang ◽  
Xin Qiao Yu
Keyword(s):  
Hardware Implementation ◽  
Ldpc Codes ◽  
Low Complexity ◽  
Scaling Factor ◽  
Computation Complexity ◽  
Decoding Complexity ◽  
Decoding Algorithms ◽  
Hardware Resource ◽  
Simulation Results ◽  
Ber Performance

Decoding algorithms with strong practical value not only have good decoding performance, but also have the computation complexity as low as possible. For this purpose, the paper points out the modified min-sum decoding algorithm(M-MSA). On the condition of no increasing in the decoding complexity, it makes the error-correcting performance improved by adding the appropriate scaling factor based on the min-sum algorithm(MSA), and it is very suitable for hardware implementation. Simulation results show that this algorithm has good BER performance, low complexity and low hardware resource utilization, and it would be well applied in the future.

A BP Decoding Algorithm Based on Nodes Residual for LDPC Codes and its Hardware Implementation

2011 ◽  
Vol 128-129 ◽  
pp. 7-10
Author(s):  
Zhong Xun Wang ◽  
Xing Cheng Wang ◽  
Fang Qiang Zhu
Keyword(s):  
Hardware Implementation ◽  
Belief Propagation ◽  
Dynamic Scheduling ◽  
Ldpc Codes ◽  
Ldpc Code ◽  
Low Complexity ◽  
Decoding Algorithm ◽  
Fast Decoding ◽  
Good For

We researched BP decoding algorithm based on variable-to-check information residual for LDPC code (VC-RBP) in this paper. It is a dynamic scheduling belief propagation using residuals, and has some advantages，such as fast decoding, good performance, and low complexity. It is similar to residual belief propagation (RBP),but has some difference in computing the residual message. This paper further optimized the new algorithm on DSP of TMS320dm6446, and it is good for hardware implementation.

Hybrid Decoding Algorithm for LDPC Codes with Circles

2011 ◽  
Vol 271-273 ◽  
pp. 258-263
Author(s):  
Li Shuang Hu ◽  
Ming Shan Liu ◽  
Yuan Zhou ◽  
Yang Sun
Keyword(s):  
Error Rate ◽  
Belief Propagation ◽  
Additive White Gaussian Noise ◽  
Ldpc Codes ◽  
Error Correcting Codes ◽  
Parity Check ◽  
Likelihood Ratios ◽  
Decoding Algorithms ◽  
Variable Node ◽  
Check Node

At present, Low-Density Parity-Check (LDPC) codes widely used in many fields of communications have the best performance of all the Error Correcting Codes (ECC). This paper mainly studies the decoding algorithms of LDPC. It proposes an improved algorithm which is named Check-Variable nodes Hybrid(CVH) algorithm on the basis of the existing algorithms. The CVH algorithm can reduce the computational complexity during the check-node update while overcome with the correlation between the variable-node news in a code with circles. As well as, comparing with the original algorithms the performance of the new one saves 0.1 and 0.3 dB than Log-likelihood Ratios (LLR) Belief Propagation (BP) and BP - based algorithms under Additive White Gaussian Noise (AWGN) channel when the Bit Error Rate (BER) falls to through the simulation. This point shows that this algorithm can increase the decoding performance and reduce the error rate effectively.

Bit-Reliability Based Low-Complexity Decoding Algorithms for Non-Binary LDPC Codes

2014 ◽  
Vol 62 (12) ◽  
pp. 4230-4240 ◽  
Author(s):  
Qin Huang ◽  
Mu Zhang ◽  
Zulin Wang ◽  
Lu Wang
Keyword(s):  
Ldpc Codes ◽  
Low Complexity ◽  
Decoding Algorithms

scholarly journals Mapper and Demapper for LDPC-Coded Systems

2012 ◽  
pp. 104-109
Author(s):  
U. Kiran ◽  
V. Ugendar
Keyword(s):  
Ldpc Codes ◽  
Low Complexity ◽  
Error Correcting Codes ◽  
Modulation Scheme ◽  
Finite Precision ◽  
Decoding Algorithms ◽  
Mapping Strategy ◽  
Coded Systems ◽  
Approximate Expressions ◽  
The Ideal

Low Density Parity Check (LDPC) codes are state-of-art error correcting codes, included in several standards for broadcast transmissions. Iterative softdecision decoding algorithms for LDPC codes reach excellent error correction capability; their performance, however, is strongly affected by finite-precision issues in the representation of inner variables. Great attention has been paid, in recent literature, to the topic of quantization for LDPC decoders, but mostly focusing on binary modulations and analyzing finite precision effects in a disaggregrated manner, i.e., considering separately each block of the receiver. Modern telecommunication standards, instead, often adopt high order modulation schemes, e.g. M-QAM, with the aim to achieve large spectral efficiency. This puts additional quantization problems, that have been poorly debated in previous literature. This paper discusses the choice of suitable quantization characteristics for both the decoder messages and the received samples in LDPC-coded systems using M-QAM schemes. The analysis involves also the demapper block, that provides initial likelihood values for the decoder, by relating its quantization strategy with that of the decoder. A signal label for a signal in a 2m-ary modulation scheme is simply the m-bit pattern assigned to the signal. A mapping strategy refers to the grouping of bits within a codeword, where each mbit group is used to select a 2m-ary signal in accordance with the signal labels. The most obvious mapping strategy is to use each group of m consecutive bits to select a signal. . We will call this the consecutive-bit (CB) mapping strategy. An alternative strategy is the bit-reliability (BR) mapping strategy which will be described below. A new demapper version, based on approximate expressions, is also presented, that introduces a slight deviation from the ideal case but yields a low complexity hardware implementation.

scholarly journals Flexible soft-output decoding of polar codes

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Sunghoon Lee ◽  
Jooyoun Park ◽  
Il-Min Kim ◽  
Jun Heo
Keyword(s):  
Belief Propagation ◽  
Low Complexity ◽  
Low Latency ◽  
Polar Codes ◽  
High Complexity ◽  
Decoding Algorithms ◽  
Long Latency ◽  
System Requirement ◽  
System Requirements ◽  
High Computational Complexity

AbstractIn this research, we study soft-output decoding of polar codes. Two representative soft-output decoding algorithms are belief propagation (BP) and soft cancellation (SCAN). The BP algorithm has low latency but suffers from high computational complexity. On the other hand, the SCAN algorithm, which is proposed for reduced complexity of soft-output decoding, achieves good decoding performance but suffers from long latency. These two algorithms are suitable only for two extreme cases that need very low latency (but with high complexity) or very low complexity (but with high latency). However, many practical systems may need to work for the moderate cases (i.e., not too high latency and not too high complexity) rather than two extremes. To adapt to the various needs of the systems, we propose a very flexible soft-output decoding framework of polar codes. Depending on which system requirement is most crucial, the proposed scheme can adapt to the systems by controlling the level of parallelism. Numerical results demonstrate that the proposed scheme can effectively adapt to various system requirements by changing the level of parallelism.

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