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Disentangled Information Bottleneck Guided Privacy-Protective joint source and channel coding for Image Transmission

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IEEE TRANSACTIONS ON COMMUNICATIONS 2024年第11期72卷 6992-7005页

作者： Sun, Lunan Yang, Yang Chen, Mingzhe Guo, Caili Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Beijing Key Lab Network Syst Architecture & Conver Beijing 100876 Peoples R China Univ Miami Dept Elect & Comp Engn Coral Gables FL 33146 USA Univ Miami Inst Data Sci & Comp Coral Gables FL 33146 USA Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Beijing Lab Adv Informat Networks Beijing 100876 Peoples R China

joint source and channel coding (JSCC) has attracted increasing attention in semantic communications. However, JSCC is vulnerable to privacy issues due to the high relevance between the source image and channel input. In this paper, we propose a disentangled information bottleneck guided privacy-protective JSCC (DPJSCC) for image transmission, which aims at protecting private information and achieving superior image transmission performance. In particular, we propose a disentangled information bottleneck objective to compress the private information in public subcodewords and improve the reconstruction quality simultaneously. To optimize JSCC neural networks using the proposed objective, we derive a differentiable estimation based on variational approximation and the density-ratio trick. Additionally, we design a password-based privacy-protective algorithm that encrypts the private subcodewords, achieving joint optimization with JSCC neural networks. The proposed algorithm involves an encryptor for encrypting private information and a decryptor for recovering it at the legitimate receiver. A loss function is derived based on the maximum entropy principle for jointly training the encryptor, decryptor, and JSCC decoder to maximize eavesdropping uncertainty and improve reconstruction quality. Experimental results show that DPJSCC reduces eavesdropping accuracy on private information by up to 18% and decreases inference time by 10%.

关键词： Image reconstruction Neural networks Image communication Encryption Distortion Protection Noise measurement joint source and channel coding information bottleneck semantic communication privacy protection

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joint source and channel coding Using Double Polar Codes

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IEEE COMMUNICATIONS LETTERS 2021年第9期25卷 2810-2814页

作者： Dong, Yanfei Niu, Kai Dai, Jincheng Wang, Sen Yuan, Yifei Beijing Univ Posts & Telecommun Key Lab Universal Wireless Commun Minist Educ Beijing 100876 Peoples R China

In this letter, a double polar code (D-Polar) for joint source and channel coding (JSCC) is proposed, in which the source compress is implemented by a polar code, the channel error correction is performed by a systematic polar code. Furthermore, a turbo-like belief propagation (TL-BP) decoder consisted of a channel BP decoder and a source BP decoder is proposed for joint source and channel decoding in the receiver. In this TL-BP decoder, the soft information is exchanged between the channel BP decoder and the source BP decoder so as to improve the efficiency of channel decoding in utilizing the source information residual in the compressed bits. Simulation results show that the performance of the proposed D-Polar JSCC scheme with TL-BP decoder is significantly improved compared with the existing source-channel joint polarization scheme.

关键词： Decoding Polar codes Systematics Iterative decoding channel coding source coding Simulation joint source and channel coding double polar codes turbo-like belief propagation decoder

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Adaptive Information Bottleneck Guided joint source and channel coding for Image Transmission

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2023年第8期41卷 2628-2644页

作者： Sun, Lunan Yang, Yang Chen, Mingzhe Guo, Caili Saad, Walid Poor, H. Vincent Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Beijing Key Lab Network Syst Architecture & Conver Beijing 100876 Peoples R China Univ Miami Dept Elect & Comp Engn Coral Gables FL 33146 USA Univ Miami Inst Data Sci & Comp Coral Gables FL 33146 USA Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Beijing Lab Adv Informat Net works Beijing 100876 Peoples R China Virginia Tech Bradley Dept Elect & Comp Engn Wireless VT Grp Arlington VA 24061 USA Princeton Univ Dept Elect & Comp Engn Princeton NJ 08544 USA

joint source and channel coding (JSCC) for image transmission has attracted increasing attention due to its robustness and high efficiency. However, the existing deep JSCC research mainly focuses on minimizing the distortion between the transmitted and received information under a fixed number of available channels. Therefore, the transmitted rate may be far more than its required minimum value. In this paper, an adaptive information bottleneck (IB) guided joint source and channel coding (AIB-JSCC) method is proposed for image transmission. The goal of AIB-JSCC is to reduce the transmission rate while improving the image reconstruction quality. In particular, a new IB objective for image transmission is proposed so as to minimize the distortion and the transmission rate. A mathematically tractable lower bound on the proposed objective is derived, and then, adopted as the loss function of AIB-JSCC. To trade off compression and reconstruction quality, an adaptive algorithm is proposed to adjust the hyperparameter of the proposed loss function dynamically according to the distortion during the training. Experimental results show that AIB-JSCC can significantly reduce the required amount of transmitted data and improve the reconstruction quality and downstream task accuracy.

关键词： & nbsp Information bottleneck joint source and channel coding image transmission

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channel-Aware Deep joint source-channel coding for Multi-Task Oriented Semantic Communication

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IEEE WIRELESS COMMUNICATIONS LETTERS 2025年第5期14卷 1521-1525页

作者： Wang, Biqi Gu, Run Xu, Wei Jiang, Feng Li, Mengyu Wang, Shen Southeast Univ Natl Mobile Commun Res Lab Nanjing 211189 Peoples R China Purple Mt Labs Pervas Commun Res Ctr Nanjing 211111 Peoples R China China Mobile Grp Design Inst Co Ltd Wireless Network Dept Beijing 100080 Peoples R China

Existing deep learning (DL)-based semantic communication generally employs deep neural networks (DNNs) for semantic extraction at a fixed dimension and incorporates channel state information (CSI) to facilitate semantic transmission. However, the optimal dimension of the semantic information to transmit varies with wireless channel conditions, trading off between channel uses and performance depending on the channel condition. To strike the balance, this letter proposes a channel-aware deep joint source-channel coding (CA-DJSCC) for multi-task oriented semantic communication. Specifically, we formulate an optimization problem to characterize the intricate and hard-to-quantify relationship between the channel condition and the optimal dimension. To achieve the channel-adaptive dimension, we develop a joint source and channel encoder, pruning elements based on semantic importance. Correspondingly, we also design a joint source and channel decoder, introducing a reference signal to enhance the multi-task performance. Simulation results demonstrate that the CA-DJSCC achieves superior performance in terms of both image reconstruction and classification tasks, with over 44.1% reduction in average channel uses compared to typical baselines.

关键词： Semantics Multitasking Signal to noise ratio Vectors Data mining Feature extraction Decoding Visualization Semantic communication Training joint source and channel coding multi-task execution deep learning

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joint source-channel coding for 6G Communications

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China Communications 2022年第3期19卷 101-115页

作者： Yanfei Dong Jincheng Dai Kai Niu Sen Wang Yifei Yuan The Key Laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China China Mobile Research Institute Beijing 100876China

In order to provide ultra low-latency and high energy-efficient communication for intelligences,the sixth generation(6G)wireless communication networks need to break out of the dilemma of the depleting gain of the separated optimization *** this context,this paper provides a comprehensive tutorial that overview how joint source-channel coding(JSCC)can be employed for improving overall system *** the purpose,we first introduce the communication requirements and performance metrics for ***,we provide an overview of the source-channel separation theorem and why it may not hold in practical *** addition,we focus on two new JSCC schemes called the double low-density parity-check(LDPC)codes and the double polar codes,respectively,giving their detailed coding and decoding processes and corresponding performance *** a nutshell,this paper constitutes a tutorial on the JSCC scheme tailored to the needs of future 6G communications.

关键词： 6G joint source and channel coding doubel LDPC codes doubel polar codes

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VQ-VAE Empowered Wireless Communication for joint source-channel coding and Beyond

VQ-VAE Empowered Wireless Communication for Joint Source-Cha...

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IEEE Conference on Global Communications (IEEE GLOBECOM) - Intelligent Communications for Shared Prosperity

作者： Nemati, Mahyar Park, Jihong Choi, Jinho Deakin Univ Sch Informat Technol Geelong Vic Australia

ISBN: (纸本)9798350310900

Vector Quantized Variational Autoencoder (VQ-VAE) has shown promise in representing diverse and complex data distributions in deep learning, making it a potential solution for various applications including wireless communications. In this paper, we propose a joint source-channel coding scheme based on VQ-VAE for point-to-point wireless communication. Our approach leverages the dependence of the encoder and decoder on a given dataset and channel conditions to develop efficient encoding and decoding schemes, leading to improved reliability and efficiency even in the presence of noisy wireless channels. We demonstrate the effectiveness of our proposed approach through extensive simulations in handling realistic wireless communication scenarios. In addition, we discuss potential connections to semantic communication and highlight the secure and energy-efficient nature of our approach.

关键词： joint source and channel coding Lossy Compression Noisy channels VQ-VAE

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Deep joint source-channel coding for Wireless Image Transmission with Entropy-Aware Adaptive Rate Control

Deep Joint Source-Channel Coding for Wireless Image Transmis...

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IEEE Conference on Global Communications (IEEE GLOBECOM) - Intelligent Communications for Shared Prosperity

作者： Chen, Weixuan Chen, Yuhao Yang, Qianqian Huang, Chongwen Wang, Qian Zhang, Zhaoyang Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310007 Peoples R China Zhejiang Univ Coll Control Sci & Engn Hangzhou 310007 Peoples R China Zhejiang Univ Technol Coll Informat Engn Hangzhou 310023 Peoples R China

ISBN: (纸本)9798350310900

Adaptive rate control for deep joint source and channel coding (JSCC) is considered as an effective approach to transmit sufficient information in scenarios with limited communication resources. We propose a deep JSCC scheme for wireless image transmission with entropy-aware adaptive rate control, using a single deep neural network to support multiple rates and automatically adjust the rate based on the feature maps of the input image and their entropy, as well as the channel conditions. In particular, we maximize the entropy of the feature maps to increase the average information carried by each transmitted symbol during the training. We further decide which feature maps should be activated based on their entropy, which improves the efficiency of the transmitted symbols. We also propose a pruning module to remove less important pixels in the activated feature maps in order to further improve transmission efficiency. The experimental results demonstrate that our proposed scheme learns an effective rate control strategy that reduces the required channel bandwidth while preserving the quality of the reconstructed images.

关键词： joint source and channel coding adaptive rate control

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Texture-Distortion-Constrained joint source-channel coding of Multi-View Video Plus Depth-Based 3D Video

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2019年第11期29卷 3326-3340页

作者： Gao, Pan Xiang, Wei Liang, Dong Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol Nanjing 211106 Jiangsu Peoples R China Trinity Coll Dublin Sch Comp Sci & Stat Dublin D02 PN40 2 Ireland James Cook Univ Coll Sci & Engn Cairns Qld 4870 Australia

A novel joint source and channel coding scheme tailored to 3D video is proposed in this paper to minimize the end-to-end view synthesis distortion within a given total bit rate for both texture and depth as well as a maximum tolerable distortion constraint for texture. First, we formulate a joint texture and depth coding mode selection strategy for error-resilient source coding of multi-view video plus depth-based 3D video through using the Lagrange multiplier method. Then, by considering the effect of residual errors after channel coding, we evolve to a more general formulation that jointly optimizes error-resilient source coding and channel coding in an integrated manner for unequal error protection between texture and depth, for which a theoretic solution using a proposed dual-trellis is derived. Finally, we extend the general formulation by including the texture distortion constraint. We show how to optimize the view synthesis quality while simultaneously catering to the texture quality constraint. Experimental results demonstrate the proposed algorithm has much better performance than existing related work.

关键词： joint source and channel coding joint texture and depth map coding texture distortion constraint 3D video transmission

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joint source, channel, and Space-Time coding of Progressive Bitstream in MIMO channels

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IEEE TRANSACTIONS ON COMMUNICATIONS 2020年第4期68卷 2551-2565页

作者： Chang, Seok-Ho Shin, Meesue Kim, Sang-Hyo Konkuk Univ Seoul 05029 South Korea GS Caltex Corp Seoul 06141 South Korea Sungkyunkwan Univ Coll Informat & Commun Engn Suwon 16419 South Korea

The optimization of joint source and channel coding for a sequence of numerous progressive packets has been a challenging problem. Further, the problem becomes more complicated if the space-time coding is also involved with the optimization in a multiple-input multiple-output (MIMO) system. This is because the number of ways of jointly assigning channel codes and space-time codes to progressive packets is much larger than that of solely assigning channel codes to the packets. To our knowledge, there is no complete and feasible solution for the optimization of joint source, channel, and space-time coding of progressive packets. This paper applies a parametric approach to address such a highly nonlinear optimization problem in MIMO systems. We use the parametric methodology and derive some relevant properties, which are exploited to propose an efficient optimization method where the joint assignment of channel codes and space-time codes to the packets can be optimized in a packet-by-packet manner. As a result, the computational complexity of the proposed method linearly increases in the number of packets, whereas that of the exhaustive search exponentially increases in the number of packets. The numerical results show that the proposed method significantly improves the peak-signal-to-noise ratio performance of the conventional rate-based optimal solution in a MIMO system.

关键词： Space-time codes MIMO communication Multiplexing Optimization Modulation Encoding Streaming media Diagonal Bell Labs space time architecture (D-BLAST) joint source and channel coding multiple-input multiple-output (MIMO) optimization orthogonal space-time block codes (OSTBC) progressive source space-time codes vertical Bell Labs space-time architecture (V-BLAST)

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On joint source-channel coding for Correlated sources Over Multiple-Access Relay channels

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IEEE TRANSACTIONS ON INFORMATION THEORY 2014年第10期60卷 6231-6253页

作者： Murin, Yonathan Dabora, Ron Guenduez, Deniz Ben Gurion Univ Negev Dept Elect & Comp Engn IL-84110 Beer Sheva Israel Univ London Imperial Coll Sci Technol & Med Dept Elect & Elect Engn London SW7 2AZ England

We study the transmission of correlated sources over discrete memoryless (DM) multiple-access-relay channels (MARCs), in which both the relay and the destination have access to side information arbitrarily correlated with the sources. As the optimal transmission scheme is an open problem, in this paper, we propose a new joint source-channel coding scheme based on a novel combination of the correlation preserving mapping (CPM) technique with Slepian-Wolf (SW) source coding, and obtain the corresponding sufficient conditions. The proposed coding scheme is based on the decode-and-forward strategy, and utilizes CPM for encoding information simultaneously to the relay and the destination, whereas the cooperation information from the relay is encoded via SW source coding. It is shown that there are cases in which the new scheme strictly outperforms the schemes available in the literature. This is the first instance of a source-channel code that uses CPM for encoding information to two different nodes (relay and destination). In addition to sufficient conditions, we present three different sets of single-letter necessary conditions for reliable transmission of correlated sources over DM MARCs. The newly derived conditions are shown to be at least as tight as the previously known necessary conditions.

关键词： Multiple-access relay channel joint source and channel coding correlation preserving mapping correlated sources side information decode-and-forward

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