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17 pages, 1117 KB

Open AccessArticle

High-Efficiency Lossy Source Coding Based on Multi-Layer Perceptron Neural Network

by Yuhang Wang, Weihua Chen, Linjing Song, Zhiping Xu, Dan Song and Lin Wang

Entropy 2025, 27(10), 1065; https://doi.org/10.3390/e27101065 - 14 Oct 2025

Viewed by 141

With the rapid growth of data volume in sensor networks, lossy source coding systems achieve high–efficiency data compression with low distortion under limited transmission bandwidth. However, conventional compression algorithms rely on a two–stage framework with high computational complexity and frequently struggle to balance [...] Read more.

With the rapid growth of data volume in sensor networks, lossy source coding systems achieve high–efficiency data compression with low distortion under limited transmission bandwidth. However, conventional compression algorithms rely on a two–stage framework with high computational complexity and frequently struggle to balance compression performance with generalization ability. To address these issues, an end–to–end lossy compression method is proposed in this paper. The approach integrates an enhanced belief propagation algorithm with a multi–layer perceptron neural network, aiming to introduce a novel joint optimization architecture described as “encoding–structured encoding–decoding”. In addition, a quantization module incorporating random perturbation and the straight–through estimator is designed to address the non–differentiability in the quantization process. Simulation results demonstrate that the proposed system significantly improves compression performance while offering superior generalization and reconstruction quality. Furthermore, the designed neural architecture is both simple and efficient, reducing system complexity and enhancing feasibility for practical deployment. Full article

(This article belongs to the Special Issue Next-Generation Channel Coding: Theory and Applications)

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16 pages, 446 KB

Open AccessArticle

Design of Low-Latency Layered Normalized Minimum Sum Low-Density Parity-Check Decoding Based on Entropy Feature for NAND Flash-Memory Channel

by Yingge Li and Haihua Hu

Entropy 2024, 26(9), 781; https://doi.org/10.3390/e26090781 - 12 Sep 2024

Cited by 1 | Viewed by 1570

Abstract

As high-speed big-data communications impose new requirements on storage latency, low-density parity-check (LDPC) codes have become a widely used technology in flash-memory channels. However, the iterative LDPC decoding algorithm faces a high decoding latency problem due to its mechanism based on iterative message [...] Read more.

As high-speed big-data communications impose new requirements on storage latency, low-density parity-check (LDPC) codes have become a widely used technology in flash-memory channels. However, the iterative LDPC decoding algorithm faces a high decoding latency problem due to its mechanism based on iterative message transmission. Motivated by the unbalanced bit reliability of codeword, this paper proposes two technologies, i.e., serial entropy feature-based layered normalized min-sum (S-EFB-LNMS) decoding and parallel entropy feature-based layered normalized min-sum (P-EFB-LNMS) decoding. First, we construct an entropy feature vector that reflects the real-time bit reliability of the codeword. Then, the reliability of the output information of the layered processing unit (LPU) is evaluated by analyzing the similarity between the check matrix and the entropy feature vector. Based on this evaluation, we can dynamically allocate and schedule LPUs during the decoding iteration process, thereby optimizing the entire decoding process. Experimental results show that these techniques can significantly reduce decoding latency. Full article

(This article belongs to the Special Issue Advanced New Physical Layer Technologies for Next-Generation Wireless Communications)

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17 pages, 836 KB

Open AccessArticle

Bilayer LDPC Codes Combined with Perturbed Decoding for MLC NAND Flash Memory

by Lingjun Kong, Haiyang Liu, Wentao Hou and Chao Meng

Entropy 2024, 26(1), 54; https://doi.org/10.3390/e26010054 - 8 Jan 2024

Cited by 2 | Viewed by 2353

Abstract

This paper presents a coding scheme based on bilayer low-density parity-check (LDPC) codes for multi-level cell (MLC) NAND flash memory. The main feature of the proposed scheme is that it exploits the asymmetric properties of an MLC flash channel and stores the extra [...] Read more.

This paper presents a coding scheme based on bilayer low-density parity-check (LDPC) codes for multi-level cell (MLC) NAND flash memory. The main feature of the proposed scheme is that it exploits the asymmetric properties of an MLC flash channel and stores the extra parity-check bits in the lower page, which are activated only after the decoding failure of the upper page. To further improve the performance of the error correction, a perturbation process based on the genetic algorithm (GA) is incorporated into the decoding process of the proposed coding scheme, which can convert uncorrectable read sequences into error-correctable regions of the corresponding decoding space by introducing GA-trained noises. The perturbation decoding process is particularly efficient at low program-and-erase (P/E) cycle regions. The simulation results suggest that the proposed bilayer LDPC coding scheme can extend the lifetime of MLC NAND flash memory up to 10,000 P/E cycles. The proposed scheme can achieve a better balance between performance and complexity than traditional single LDPC coding schemes. All of these findings indicate that the proposed coding scheme is suitable for practical purposes in MLC NAND flash memory. Full article

(This article belongs to the Special Issue Advances in Information and Coding Theory II)

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11 pages, 356 KB

Open AccessCommunication

Belief Propagation Optimization for Lossy Compression Based on Gaussian Source

by Huan Deng, Dan Song, Zhiping Xu, Yanglong Sun and Lin Wang

Sensors 2023, 23(21), 8805; https://doi.org/10.3390/s23218805 - 29 Oct 2023

Cited by 1 | Viewed by 1443

Abstract

In the Internet of Things, sensor nodes collect environmental information and utilize lossy compression for saving storage space. To achieve this objective, high-efficiency compression of the continuous source should be studied. Different from existing schemes, lossy source coding is implemented based on the [...] Read more.

In the Internet of Things, sensor nodes collect environmental information and utilize lossy compression for saving storage space. To achieve this objective, high-efficiency compression of the continuous source should be studied. Different from existing schemes, lossy source coding is implemented based on the duality principle in this work. Referring to the duality principle between the lossy source coding and the channel decoding, the belief propagation (BP) algorithm is introduced to realize lossy compression based on a Gaussian source. In the BP algorithm, the log-likelihood ratios (LLRs) are iterated, and their iteration paths follow the connecting relation between the check nodes and the variable nodes in the protograph low-density parity-check (P-LDPC) code. During LLR iterations, the trapping set is the main factor that influences compression performance. We propose the optimized BP algorithms to weaken the impact of trapping sets. The simulation results indicate that the optimized BP algorithms obtain better distortion–rate performance. Full article

(This article belongs to the Section Communications)

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14 pages, 865 KB

Open AccessArticle

Designing Protograph LDPC Codes for Differential Chaotic Bit-Interleaved Coded Modulation System for Underwater Acoustic Communications

by Zhiping Xu, Qiwang Chen, Yang Li, Guofa Cai, Lixiong Lin, Jiachun Zheng and Yanglong Sun

J. Mar. Sci. Eng. 2023, 11(5), 914; https://doi.org/10.3390/jmse11050914 - 24 Apr 2023

Cited by 2 | Viewed by 2435

Abstract

Underwater acoustic (UWA) communications face many challenges, such as large multipath delay, severe fading and the time-varying distortions. Chaotic modulations have shown advantages in UWA communications, but the reliability of current chaotic modulations is still not guaranteed. In this paper, a short-length protograph [...] Read more.

Underwater acoustic (UWA) communications face many challenges, such as large multipath delay, severe fading and the time-varying distortions. Chaotic modulations have shown advantages in UWA communications, but the reliability of current chaotic modulations is still not guaranteed. In this paper, a short-length protograph low-density parity-check (P-LDPC) code design framework for the differential chaotic bit-interleaved coded modulation (DC-BICM) system for UWA communication is proposed. This design framework, considering the requirements of short codes in UWA communications, integrates the DC-BICM system, UWA channel and the differential evolutionary code searching algorithm. Through this design framework, the optimized short P-LDPC code can be obtained. Simulation results show that the DC-BICM system with the proposed P-LDPC code can obtain more than 0.48 dB coding gain and reduce 32.6%~69.5% of the average number of iterations compared with the counterparts. Moreover, the reconstructed underwater image with the proposed P-LDPC code is clearest with the highest peak-signal-noise ratio value when compared with counterparts. Full article

(This article belongs to the Special Issue Underwater Perception and Sensing with Robotic Sensors and Networks)

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15 pages, 693 KB

Open AccessArticle

Lossy P-LDPC Codes for Compressing General Sources Using Neural Networks

by Jinkai Ren, Dan Song, Huihui Wu and Lin Wang

Entropy 2023, 25(2), 252; https://doi.org/10.3390/e25020252 - 30 Jan 2023

Cited by 3 | Viewed by 2095

Abstract

It is challenging to design an efficient lossy compression scheme for complicated sources based on block codes, especially to approach the theoretical distortion-rate limit. In this paper, a lossy compression scheme is proposed for Gaussian and Laplacian sources. In this scheme, a new [...] Read more.

It is challenging to design an efficient lossy compression scheme for complicated sources based on block codes, especially to approach the theoretical distortion-rate limit. In this paper, a lossy compression scheme is proposed for Gaussian and Laplacian sources. In this scheme, a new route using “transformation-quantization” was designed to replace the conventional “quantization-compression”. The proposed scheme utilizes neural networks for transformation and lossy protograph low-density parity-check codes for quantization. To ensure the system’s feasibility, some problems existing in the neural networks were resolved, including parameter updating and the propagation optimization. Simulation results demonstrated good distortion-rate performance. Full article

(This article belongs to the Special Issue Advances in Information and Coding Theory)

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11 pages, 429 KB

Open AccessArticle

Protograph Designing of P-LDPC Codes via M³ Method

by Dan Song, Meiyuan Miao and Lin Wang

Entropy 2023, 25(2), 232; https://doi.org/10.3390/e25020232 - 27 Jan 2023

Viewed by 2307

Abstract

Recently, a mesh model-based merging (M

^{3}

) method and four basic graph models were proposed to construct the double protograph low-density parity-check (P-LDPC) code pair of the joint source channel coding (JSCC). Designing the protograph (mother code) of the P-LDPC code with [...] Read more.

Recently, a mesh model-based merging (M

^{3}

) method and four basic graph models were proposed to construct the double protograph low-density parity-check (P-LDPC) code pair of the joint source channel coding (JSCC). Designing the protograph (mother code) of the P-LDPC code with both a good waterfall region and lower error floor is a challenge, and few works have existed until now. In this paper, the single P-LDPC code is improved to further verify the availability of the M

^{3}

method, and its structure is different from the channel code in the JSCC. This construction technique yields a family of new channel codes with lower power consumption and higher reliability. The structured design and better performance demonstrate that the proposed code is hardware-friendly. Full article

(This article belongs to the Special Issue Advances in Information and Coding Theory)

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13 pages, 1089 KB

Open AccessArticle

The Efficient Design of Lossy P-LDPC Codes over AWGN Channels

by Runfeng Wang, Sanya Liu, Huihui Wu and Lin Wang

Electronics 2022, 11(20), 3337; https://doi.org/10.3390/electronics11203337 - 17 Oct 2022

Cited by 3 | Viewed by 1860

Abstract

Considering the high compression requirements of transmission, lossy block codes are particularly concerned due to their good compression performance and simple implementation. This paper investigates and analyzes the distortion rate performance of protograph LDPC (P-LDPC) codes for Bernoulli sources over AWGN channels. We [...] Read more.

Considering the high compression requirements of transmission, lossy block codes are particularly concerned due to their good compression performance and simple implementation. This paper investigates and analyzes the distortion rate performance of protograph LDPC (P-LDPC) codes for Bernoulli sources over AWGN channels. We first analytically establish the connection between the parity check matrix of a P-LDPC code and the extra distortion caused by the noisy channels. It was found that the additional distortion related to channel noise increases with the rising total degree of a parity check matrix. Further, two design algorithms are proposed for optimizing lossy multirate P-LDPC codes, considering the effect of noisy channels. Finally, simulation results demonstrate the robustness of the optimized P-LDPC codes over noisy channels. Full article

(This article belongs to the Special Issue Multirate and Multicarrier Communication)

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15 pages, 3552 KB

Open AccessArticle

New Unequal Error Protection Strategy for Image Transmission Based on Bilayer-Lengthened PLDPC Code in Half-Duplex Relay System

by Tian Gao, Min Xiao, Pingping Chen and Diyan Gao

Symmetry 2022, 14(8), 1662; https://doi.org/10.3390/sym14081662 - 11 Aug 2022

Cited by 3 | Viewed by 1804

Abstract

To reduce the waste of energy in communications, unequal error protection (UEP) is used to provide asymmetric protection for messages with different levels of importance. This paper proposes new efficient strategies of UEP based on bilayer protograph-based low-density parity check (PLDPC) codes in [...] Read more.

To reduce the waste of energy in communications, unequal error protection (UEP) is used to provide asymmetric protection for messages with different levels of importance. This paper proposes new efficient strategies of UEP based on bilayer protograph-based low-density parity check (PLDPC) codes in decoding-and-forward (DF) relay systems. In particular, we jointly utilize source coding and channel coding to design UEP strategies and then save transmission energy. According to the different levels of importance of discrete cosine transform (DCT) coefficients of image and variance statistical characteristics of image sub-blocks, bilayer-lengthened PLDPC codes are exploited to protect the transmitted image information with different importance levels at the half-duplex relay system. In the end, the simulation result shows that the proposed UEP schemes achieve excellent performance gains compared to conventional equal error protection (EEP) scheme. Additionally, the complexity analysis of the UEP strategies is given. Full article

(This article belongs to the Special Issue Optimization and Applications of Modern Wireless Networks and Symmetry)

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