A Novel LLR-BP Algorithm for LDPC Codes Based on Taylor Series and Least Squares

2013 ◽  
Vol 462-463 ◽  
pp. 193-197
Author(s):  
Xing Ru Zhang ◽  
Jian Ping Li ◽  
Chao Shi Cai
Keyword(s):  
Least Squares ◽  
Taylor Series ◽  
Belief Propagation ◽  
Signal To Noise Ratio ◽  
Ldpc Codes ◽  
Low Complexity ◽  
Significant Loss ◽  
Bp Algorithm ◽  
High Signal ◽  
Decoding Algorithm

An effective log-likelihood-ratio-based belief propagation (LLR-BP) algorithm is proposed. It can reduce computational complexity of decoding algorithm for Low Density Parity Check (LDPC) codes. By using the Taylor series and least squares, high order multiplication based on the hyperbolic tangent (tanh) rule is converted to a first-order multiplication and addition after simplification. Moreover, all the logarithmic and exponential operations disappear without significant loss of the decoding performance. The simulation results show that the performance of the proposed scheme is similar to the general LLR-BP. In particular, we show that the modified algorithm with low complexity can achieve better BER than the other decoding algorithm in high signal-to-noise ratio region.

scholarly journals A Low-Complexity Ordered Statistics Decoding Algorithm for Short Polar Codes

2019 ◽  
Vol 9 (5) ◽  
pp. 831
Author(s):  
Yusheng Xing ◽  
Guofang Tu
Keyword(s):  
Error Correction ◽  
Error Rate ◽  
Complexity Analysis ◽  
Signal To Noise Ratio ◽  
Low Complexity ◽  
High Signal ◽  
Polar Codes ◽  
Decoding Algorithm ◽  
Low Snr ◽  
Ordered Statistics

In this paper, we propose a low-complexity ordered statistics decoding (OSD) algorithm called threshold-based OSD (TH-OSD) that uses a threshold on the discrepancy of the candidate codewords to speed up the decoding of short polar codes. To determine the threshold, we use the probability distribution of the discrepancy value of the maximal likelihood codeword with a predefined parameter controlling the trade-off between the error correction performance and the decoding complexity. We also derive an upper-bound of the word error rate (WER) for the proposed algorithm. The complexity analysis shows that our algorithm is faster than the conventional successive cancellation (SC) decoding algorithm in mid-to-high signal-to-noise ratio (SNR) situations and much faster than the SC list (SCL) decoding algorithm. Our addition of a list approach to our proposed algorithm further narrows the error correction performance gap between our TH-OSD and OSD. Our simulation results show that, with appropriate thresholds, our proposed algorithm achieves performance close to OSD’s while testing significantly fewer codewords than OSD, especially with low SNR values. Even a small list is sufficient for TH-OSD to match OSD’s error rate in short-code scenarios. The algorithm can be easily extended to longer code lengths.

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 Minimum Distance Optimization with Chord Edge Growth for High Girth Non-Binary LDPC Codes

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2161
Author(s):  
Changcai Han ◽  
Hui Li ◽  
Weigang Chen
Keyword(s):  
Minimum Distance ◽  
Signal To Noise Ratio ◽  
High Reliability ◽  
Ldpc Codes ◽  
Full Rank ◽  
Ldpc Code ◽  
Low Complexity ◽  
High Signal ◽  
Rank Condition ◽  
Potential Applications

Short or moderate-length non-binary low-density parity-check (NB-LDPC) codes have the potential applications in future low latency and high-reliability communication thanks to the strong error correction capability and parallel decoding. Because of the existence of the error floor, the NB-LDPC codes usually cannot satisfy very low bit error rate (BER) requirements. In this paper, a low-complexity method is proposed for optimizing the minimum distance of the NB-LDPC code in a progressive chord edge growth manner. Specifically, each chord edge connecting two non-adjacent vertices is added to the Hamiltonian cycle one-by-one. For each newly added chord edge, the configuration of non-zero entries corresponding to the chord edge is determined according to the so-called full rank condition (FRC) of all cycles that are related to the chord edge in the obtained subgraph. With minor modifications to the designed method, it can be used to construct the NB-LDPC codes with an efficient encoding structure. The analysis results show that the method for designing NB-LDPC codes while using progressive chord edge growth has lower complexity than traditional methods. The simulation results show that the proposed method can effectively improve the performance of the NB-LDPC code in the high signal-to-noise ratio (SNR) region. While using the proposed scheme, an NB-LDPC code with a quite low BER can be constructed with extremely low complexity.

LDPC Codes with the Layered LLR-BP Algorithm for 3GPP

2013 ◽  
Vol 462-463 ◽  
pp. 720-723
Author(s):  
Miao Miao Li ◽  
Jian Ping Li ◽  
Chao Shi Cai
Keyword(s):  
Belief Propagation ◽  
Ldpc Codes ◽  
Bp Algorithm ◽  
Parity Check ◽  
Computation Complexity ◽  
Decoding Algorithm ◽  
Absolute Value ◽  
Low Density Parity Check ◽  
Variable Node ◽  
Log Likelihood

We propose a layered log-likelihood-ratio-based belief propagation(LLR-BP)algorithm for Low Density Parity Check (LDPC)codes. In the conventional decoding algorithm, the process of decoding would be terminated when it reaches the maximum iterative number or the near-convergence is achieved. The proposed algorithm is based on the variable node information quantification and stop updating criterion thought. By dividing the absolute value of the variable node to different layers, a part of the check nodes stop the iteration before reaching the maximum iterative number to save iterative time. From the simulation results, we know that the improved decoding algorithm successively achieves lower computation complexity than the conventional one .And the layered LLR-BP algorithm is a better scheme for LDPC codes.

scholarly journals Design of Quasi-Cyclic Low Density Parity Check Decoder Using Optimized Min-Sum Algorithm

2018 ◽  
Vol 7 (03) ◽  
pp. 23781-23784
Author(s):  
Rajarshini Mishra
Keyword(s):  
Variance Estimation ◽  
Cyclic Codes ◽  
Ldpc Codes ◽  
Ldpc Code ◽  
Low Complexity ◽  
Low Density ◽  
Parity Check ◽  
Decoding Algorithm ◽  
Low Density Parity Check ◽  
Xilinx Fpga

Low-density parity-check (LDPC) have been shown to have good error correcting performance approaching Shannon’s limit. Good error correcting performance enables efficient and reliable communication. However, a LDPC code decoding algorithm needs to be executed efficiently to meet cost , time, power and bandwidth requirements of target applications. Quasi-cyclic low-density parity-check (QC-LDPC) codes are an important subclass of LDPC codes that are known as one of the most effective error controlling methods. Quasi cyclic codes are known to possess some degree of regularity. Many important communication standards such as DVB-S2 and 802.16e use these codes. The proposed Optimized Min-Sum decoding algorithm performs very close to the Sum-Product decoding while preserving the main features of the Min-Sum decoding, that is low complexity and independence with respect to noise variance estimation errors.Proposed decoder is well matched for VLSI implementation and will be implemented on Xilinx FPGA family

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.

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