Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

IEEE Vehicular Technology Conference

Robust Low Density Parity Check Decoding over Markov Gaussian Channels

Der‐Feng Tseng, Shi-Shun Lin

Published Apr 1, 2019• 2 citations
Publisher

Abstract

Communications systems suffer from impulsive in- terference, generally modeled as a memory channel to account for the inherent bursts of impulse even though conventional receivers take into account the additive white Gaussian noise only. In this paper, finite- field based constructions of Low Density Parity Check (LDPC) coding over the Markov Gaussian channel are investigated. In contrast with existing approaches assuming the impulse noise statistics, this paper proposes a modified maximum- a-priori method, which forfeits using the statistical knowledge of impulse, to estimate whether or not each transmitted symbol is corrupted by impulse noise. Subsequently, the sum-product algorithm LDPC decoder invokes a clipper to diminish impulsive interference when the channel state is identified to be impulse- corrupted. The bit error rate (BER) performance versus the signal-to-noise ratio for the proposed decoder is conducted using computer simulation. The experimental results in terms of the BER performance justified the robustness of our proposed receiver and also revealed its competitiveness with the optimal benchmark decoder in the hostile environment. Moreover, using the proposed receiver, our calibrated quasi-cyclic LDPC code is shown to slightly outperform its 5G New Radio counterpart under certain circumstances.

DOI
10.1109/vtcspring.2019.8746326

Related papers

An optimized initialization for LDPC decoding over GF(q) in impulsive noise environments

Haoqiang Liu, Hongbo Zhao, Xiaowen Chen +1 more

Modern navigation satellite communication has the characteristic of high transmitting rate. To avoid bit errors in data transmission, low density parity check (LDPC) codes are widely recognized as efficient ways for navigation communication. Conventionally, the LDPC decoding is applied for additive white Gaussian noise (AWGN) channel and degrades severely while facing the impulsive noise. However, navigation communication often suffers from impulsive interference due to the occurrence of high amplitude "spikes". At this time, the conventional Gaussian noise assumption is inadequate. The impulsive component of interference has been found to be significant which influences the reliability of transmitted information. Therefore the LDPC decoding algorithms for AWGN channel are not suitable for impulsive noise environments. Consider that LDPC codes over GF(q) perform better than binary LDPC in resisting burst errors for current navigation system, it is necessary to conduct research on LDPC codes over GF(q). In this paper, an optimized initialization by calculating posterior probabilities of received symbols is proposed for non-binary LDPC decoding on additive white Class A noise (AWAN) channel. To verify the performance of the proposed initialization, extensive experiments are performed in terms of convergence, validity, and robustness. Preliminary results demonstrate that the decoding algorithm with the optimized initialization for non-binary LDPC codes performs better than the competing methods and that of binary LDPC codes on AWAN channel.

PLoS ONE•May 6, 2021•1 citation

Finite Length Analysis of Low-Density Parity-Check Codes on Impulsive Noise Channels

Zhen Mei, Martin Johnston, Stephane Le Goff +1 more

Low-density parity-check (LDPC) codes with very long block lengths are well known for their powerful error correction, but it is not always desirable to employ long codes in communication systems, where latency is a serious issue, such as voice and video communication between multiple users. Finite length analyses of LDPC codes have already been presented in the literature for the additive white Gaussian noise channel, but in this paper, we consider the finite length analysis of LDPC codes for channels that exhibit impulsive noise. First, an exact uncoded bit error probability (BEP) of an impulsive noise channel, modeled as a symmetric α-stable (SαS) distribution, is derived. Then, to obtain the LDPC-coded performance, density evolution is applied to evaluate the asymptotic performance of LDPC codes on SαS channels and determine the threshold signal-to-noise ratio. Finally, we derive closed-form expressions for the BEP and block error probability of short LDPC codes on these channels, which are shown to match closely with simulated results on channels with different levels of impulsiveness, even for block lengths as low as 1000 b.

IEEE Access•Jan 1, 2016•9 citations

Finite State Markov Modeling of Fading Channels Towards Decoding of LDPC Codes

M. Sravan Kumar

Here we have proposed two decoding strategies of low-density parity-check (LDPC) codes over Markov noise channels with bit flipping noise. The sum-product algorithm used for decoding LDPC codes over memoryless channels is extended to include channel estimation and how much gain we obtain by doing so is simulated and verified. LDPC codes have been studied for years over memoryless channels and are known to have excellent performance. However, these codes over channels with memory is the topic of current research. Here, channels with memory are characterized by Markov modeling which is a useful busty channel model. With sufficient no. of states, they are able to model sufficient noise characteristics. We have gone for a two-state system as it shows a good compromise between complexity and performance.

arXiv:1912.09463•Oct 19, 2019•0 citations

Decoding of low-density parity check codes over finite-state binary Markov channels

Javier Garcia‐Frias

We propose a modified algorithm for decoding of low-density parity check codes over finite-state binary Markov channels. The hidden Markov model representing the channel is incorporated into the bipartite graph of the low-density parity check code, and the message passing algorithm is modified accordingly. This approach clearly outperforms systems in which the channel statistics are not exploited in the decoding, allowing reliable communication at rates which are above the capacity of a memoryless channel with the same stationary bit error probability as the Markov channel. Moreover, we introduce a joint estimation/decoding method that allows the estimation of the parameters of the channel when they are not known a priori.

IEEE International Symposium on Information Theory (ISIT)•Nov 13, 2002•19 citations

An Algebraic Construction of Quasi-Cyclic LDPC Codes Based on the Conjugates of Primitive Elements over Finite Fields

Muhammad Asif, Wuyang Zhou, Juma Saidi Ally +2 more

Recently, there have been major developments in utilizing the finite fields to construct Low-density Parity-check (LDPC) codes. In this correspondence, an algebraic approach based on the conjugates of primitive elements over finite fields to construct Quasi-Cyclic (QC) Low-Density Parity-Check codes is presented. Proposed QC-LDPC codes provide an excellent error performance with Belief Propagation (BP) decoding over an Additive White Gaussian Noise (AWGN) channel. Based on numerical results, the performance analysis shows that the proposed QC-LDPC codes perform as well as the randomly constructed Progressive edge growth (PEG) LDPC codes and algebraic QC-LDPC in the lower signal-to-noise ratio (SNR) region but outperform their counterparts in the higher SNR region. Also, the codes constructed are QC in nature, so the encoding can be done with shift register circuits having linear complexity.

IEEE International Conference on Communication Technology (ICCT)•Oct 1, 2018•3 citations

Decoding of low-density parity-check codes based on noise soft-decision over finite-state Markov channels

He-Qin Zhou

An improved decoding algorithm for low-density parity-check code(LDPC) on finite-state Markov channels was presented and the corresponding factor graph representation was given.It consists of two parts: standard sum-product algorithm(SPA) for LDPC and forward-backward(FB) algorithm for Markov channel.After each iteration for SPA,FB re-estimated the channel likelihood ratio for the next iteration of SPA based on soft decisions for noise bits from SPA.Considering more cycles in the factor graph with the introduction of the Markov channel node,the probabilistic schedule was used to update the message during the iterations for decoding.Simulation results show that the algorithm not only performs much better than the standard sum-product algorithm,but also outperforms the algorithm based on hard decisions for noise bits.

•Jan 1, 2006•0 citations
Communications systems suffer from impulsive in- terference, generally modeled as a memory channel to account for the inherent bursts of impulse even though conventional receivers take into account the additive white Gaussian noise only. In this paper, finite- field based constructions of Low Density Parity Check (LDPC) coding over the Markov Gaussian channel are investigated. In contrast with existing approaches assuming the impulse noise statistics, this paper proposes a modified maximum- a-priori method, which forfeits using the statistical knowledge of impulse, to estimate whether or not each transmitted symbol is corrupted by impulse noise. Subsequently, the sum-product algorithm LDPC decoder invokes a clipper to diminish impulsive interference when the channel state is identified to be impulse- corrupted. The bit error rate (BER) performance versus the signal-to-noise ratio for the proposed decoder is conducted using computer simulation. The experimental results in terms of the BER performance justified the robustness of our proposed receiver and also revealed its competitiveness with the optimal benchmark decoder in the hostile environment. Moreover, using the proposed receiver, our calibrated quasi-cyclic LDPC code is shown to slightly outperform its 5G New Radio counterpart under certain circumstances.
Modern navigation satellite communication has the characteristic of high transmitting rate. To avoid bit errors in data transmission, low density parity check (LDPC) codes are widely recognized as efficient ways for navigation communication. Conventionally, the LDPC decoding is applied for additive white Gaussian noise (AWGN) channel and degrades severely while facing the impulsive noise. However, navigation communication often suffers from impulsive interference due to the occurrence of high amplitude "spikes". At this time, the conventional Gaussian noise assumption is inadequate. The impulsive component of interference has been found to be significant which influences the reliability of transmitted information. Therefore the LDPC decoding algorithms for AWGN channel are not suitable for impulsive noise environments. Consider that LDPC codes over GF(q) perform better than binary LDPC in resisting burst errors for current navigation system, it is necessary to conduct research on LDPC codes over GF(q). In this paper, an optimized initialization by calculating posterior probabilities of received symbols is proposed for non-binary LDPC decoding on additive white Class A noise (AWAN) channel. To verify the performance of the proposed initialization, extensive experiments are performed in terms of convergence, validity, and robustness. Preliminary results demonstrate that the decoding algorithm with the optimized initialization for non-binary LDPC codes performs better than the competing methods and that of binary LDPC codes on AWAN channel.
Low-density parity-check (LDPC) codes with very long block lengths are well known for their powerful error correction, but it is not always desirable to employ long codes in communication systems, where latency is a serious issue, such as voice and video communication between multiple users. Finite length analyses of LDPC codes have already been presented in the literature for the additive white Gaussian noise channel, but in this paper, we consider the finite length analysis of LDPC codes for channels that exhibit impulsive noise. First, an exact uncoded bit error probability (BEP) of an impulsive noise channel, modeled as a symmetric α-stable (SαS) distribution, is derived. Then, to obtain the LDPC-coded performance, density evolution is applied to evaluate the asymptotic performance of LDPC codes on SαS channels and determine the threshold signal-to-noise ratio. Finally, we derive closed-form expressions for the BEP and block error probability of short LDPC codes on these channels, which are shown to match closely with simulated results on channels with different levels of impulsiveness, even for block lengths as low as 1000 b.
Here we have proposed two decoding strategies of low-density parity-check (LDPC) codes over Markov noise channels with bit flipping noise. The sum-product algorithm used for decoding LDPC codes over memoryless channels is extended to include channel estimation and how much gain we obtain by doing so is simulated and verified. LDPC codes have been studied for years over memoryless channels and are known to have excellent performance. However, these codes over channels with memory is the topic of current research. Here, channels with memory are characterized by Markov modeling which is a useful busty channel model. With sufficient no. of states, they are able to model sufficient noise characteristics. We have gone for a two-state system as it shows a good compromise between complexity and performance.
We propose a modified algorithm for decoding of low-density parity check codes over finite-state binary Markov channels. The hidden Markov model representing the channel is incorporated into the bipartite graph of the low-density parity check code, and the message passing algorithm is modified accordingly. This approach clearly outperforms systems in which the channel statistics are not exploited in the decoding, allowing reliable communication at rates which are above the capacity of a memoryless channel with the same stationary bit error probability as the Markov channel. Moreover, we introduce a joint estimation/decoding method that allows the estimation of the parameters of the channel when they are not known a priori.
Recently, there have been major developments in utilizing the finite fields to construct Low-density Parity-check (LDPC) codes. In this correspondence, an algebraic approach based on the conjugates of primitive elements over finite fields to construct Quasi-Cyclic (QC) Low-Density Parity-Check codes is presented. Proposed QC-LDPC codes provide an excellent error performance with Belief Propagation (BP) decoding over an Additive White Gaussian Noise (AWGN) channel. Based on numerical results, the performance analysis shows that the proposed QC-LDPC codes perform as well as the randomly constructed Progressive edge growth (PEG) LDPC codes and algebraic QC-LDPC in the lower signal-to-noise ratio (SNR) region but outperform their counterparts in the higher SNR region. Also, the codes constructed are QC in nature, so the encoding can be done with shift register circuits having linear complexity.
An improved decoding algorithm for low-density parity-check code(LDPC) on finite-state Markov channels was presented and the corresponding factor graph representation was given.It consists of two parts: standard sum-product algorithm(SPA) for LDPC and forward-backward(FB) algorithm for Markov channel.After each iteration for SPA,FB re-estimated the channel likelihood ratio for the next iteration of SPA based on soft decisions for noise bits from SPA.Considering more cycles in the factor graph with the introduction of the Markov channel node,the probabilistic schedule was used to update the message during the iterations for decoding.Simulation results show that the algorithm not only performs much better than the standard sum-product algorithm,but also outperforms the algorithm based on hard decisions for noise bits.