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.

Study of FCLSD Algorithm Performance Based on LTE System

2012 ◽  
Vol 195-196 ◽  
pp. 96-103
Author(s):  
Ke Wen Liu ◽  
Quan Liu
Keyword(s):  
High Performance ◽  
Hardware Implementation ◽  
Low Complexity ◽  
Detection Algorithm ◽  
Sphere Decoding ◽  
Mimo Detection ◽  
Decoding Algorithm ◽  
Algorithm Performance ◽  
Simulation Results ◽  
Ber Performance

Soft-output complex list sphere decoding algorithm is a low-complexity MIMO detection algorithm and its BER performance approximates that of Maximum-Likelihood. However, it has a problem of not fixed complexity, and which make it very difficult to implement. To resolve this and try best to retain the advantages of the algorithm, a modified algorithmfixed complex list sphere decoding algorithm was proposed. Based on LTE TDD system, this paper studies the performance of the FCLSD algorithm. The simulation results show that: the BER performance of the FCLSD algorithm is close to that of the CLSD algorithm. However, when the number of antennas and modulation order increasing, the FCLSD algorithm is non-constrained of spherical radius and has fixed complexity. In addition, hardware implementation of the FCLSD algorithm could be carried out by parallel processing, thereby greatly reducing the algorithm complexity. So it is a high-performance algorithm of great potential.

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.

The Design of Low Complexity Decoder Based on DVB-S2 LDPC

2012 ◽  
Vol 239-240 ◽  
pp. 911-914
Author(s):  
Zhong Xun Wang ◽  
Shuang Shuang Yin
Keyword(s):  
Hardware Implementation ◽  
Ldpc Code ◽  
Low Complexity ◽  
Bch Code ◽  
Digital Video Broadcasting ◽  
Video Broadcasting ◽  
Uniform Quantization ◽  
Point Representation ◽  
Simulation Results ◽  
Decoder Complexity

An improved codeword construction method was used to encode the BCH code and LDPC code in this paper according to the latest standard defined by digital video broadcasting standard(DVB), and moreover the data overflow problem was solved. The LDPC code was decoded by the reduced complexity Min-Sum decoding algorithm, in which the coefficient was studied. Fixed-point representation and decoder quantization were proposed and simulation results show that 6-bits and 16-bits uniform quantization can make close to the performance of unquantized decoder, which reduces the decoder complexity for hardware implementation.

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.

scholarly journals Novel Low Complexity BP Decoding Algorithms for Polar Codes: Simplifying on Non-Linear Operations

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 93
Author(s):  
Yuhuan Wang ◽  
Jianguo Li ◽  
Neng Ye ◽  
Xiangyuan Bu
Keyword(s):  
Computational Complexity ◽  
Hardware Implementation ◽  
Low Complexity ◽  
Bp Algorithm ◽  
Polar Codes ◽  
Decoding Algorithm ◽  
Hyperbolic Tangent ◽  
Decoding Algorithms ◽  
Tangent Function ◽  
Non Linear

The parallel nature of the belief propagation (BP) decoding algorithm for polar codes opens up a real possibility of high throughput and low decoding latency during hardware implementation. To address the problem that the BP decoding algorithm introduces high-complexity non-linear operations in the iterative messages update process, this paper proposes to simplify these operations and develops two novel low complexity BP decoding algorithms, namely, exponential BP (Exp-BP) decoding algorithm and quantization function BP (QF-BP) decoding algorithm. The proposed algorithms simplify the compound hyperbolic tangent function by using probability distribution fitting techniques. Specifically, the Exp-BP algorithm simplifies two types of non-linear operations into single non-linear operation using the piece-wise exponential model function, which can approximate the hyperbolic tangent function in the updating formula. The QF-BP algorithm eliminates non-linear operations using the non-uniform quantization in the updating formula, which is effective in reducing computational complexity. According to the simulation results, the proposed algorithms can reduce the computational complexity up to 50% in each iteration with a loss of less than 0.1 dB compared with the BP decoding algorithm, which can facilitate the hardware implementation.

scholarly journals SYMBOL LEVEL DECODING FOR DUO-BINARY TURBO CODES

2017 ◽  
Vol 18 (1) ◽  
pp. 111-131 ◽  
Author(s):  
Yogesh Beeharry ◽  
Tulsi Pawan Fowdur ◽  
Krishnaraj M. S. Soyjaudah
Keyword(s):  
Computational Complexity ◽  
Turbo Codes ◽  
Complexity Analysis ◽  
Error Floor ◽  
Decoding Complexity ◽  
Decoding Algorithms ◽  
Level Information ◽  
Simulation Results

This paper investigates the performance of three different symbol level decoding algorithms for Duo-Binary Turbo codes. Explicit details of the computations involved in the three decoding techniques, and a computational complexity analysis are given. Simulation results with different couple lengths, code-rates, and QPSK modulation reveal that the symbol level decoding with bit-level information outperforms the symbol level decoding by 0.1 dB on average in the error floor region. Moreover, a complexity analysis reveals that symbol level decoding with bit-level information reduces the decoding complexity by 19.6 % in terms of the total number of computations required for each half-iteration as compared to symbol level decoding.

Performance Analysis of MIA Algorithm for LDPC Codes in near Space Rain Attenuation Channel

2011 ◽  
Vol 148-149 ◽  
pp. 1576-1582
Author(s):  
Yi Dong Su ◽  
Shu Xin Chen ◽  
Hao Wu
Keyword(s):  
Iterative Decoding ◽  
High Performance ◽  
Channel Model ◽  
Ldpc Codes ◽  
Low Complexity ◽  
Rain Attenuation ◽  
Soft Decision ◽  
Decision Algorithm ◽  
Decoding Complexity ◽  
Near Space

According to the influence of grand reflector to the channel, near space Ka-band rain attenuation channel model of area coverage is improved. According to RRWBF algorithm and UMP BP-Based algorithm of LDPC codes, a mixed iterative decoding algorithm is proposed. The algorithm takes advantage of low complexity of hard-decision algorithm and high performance of soft-decision algorithm, so in near space rain attenuation channel, the decoding complexity significantly reduced when bit error rate performance does not decline. Simulation results show that in near space rain attenuation channel, MIA algorithm can reduce decoding complexity by about 30%, compare with the UMP BP-Based algorithm.

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
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