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A Cognitive Approach for Effective coding and Transmission of 3D Video

ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 2011年第1期7卷 23-23页

作者： Milani, Simone Calvagno, Giancarlo Univ Padua Dept Informat Engn I-35131 Padua Italy

Future multimedia applications will rely on the transmission of 3D video contents within heterogeneous fruition scenarios, and as a matter of fact, the reliable delivery of 3D video signals proves to be a crucial issue in such communications. To this purpose, multimedia communication experts have been designing cross-layer strategies to improve the quality of the perceived 3D experience. This article presents a new cross-layer strategy, called Cognitive source coding (CSC), that defines a new 3D video system able to identify the different elements of the 3D scene and choose the most appropriate coding strategy.

关键词： Algorithms Design Measurements Performance Cross-layer optimization source coding joint source-channel coding 3D video cognitive source coding

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The Error Probability of Generalized Perfect Codes via the Meta-Converse

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IEEE TRANSACTIONS ON INFORMATION THEORY 2019年第9期65卷 5705-5717页

作者： Vazquez-Vilar, Gonzalo Guillen i Fabregas, Albert Verdu, Sergio Univ Carlos III Madrid Signal Theory & Commun Dept Leganes 28911 Spain Gregorio Maranon Hlth Res Inst Madrid 28007 Spain Univ Pompeu Fabra Dept Informat & Commun Technol Barcelona 08018 Spain Inst Catalana Recerca & Estudis Avancats Barcelona 08010 Spain Univ Cambridge Dept Engn Cambridge CB2 1PZ England Natl Acad Engn Washington DC 20418 USA Natl Acad Sci 2101 Constitut Ave Nw Washington DC 20418 USA Australian Natl Univ Canberra ACT Australia Technion Israel Inst Technol Haifa Israel Univ Tokyo Tokyo Japan Univ Calif Berkeley Berkeley CA 94720 USA Math Sci Res Inst 1000 Centennial Dr Berkeley CA 94720 USA MIT Cambridge MA 02139 USA

We introduce a definition of perfect and quasi-perfect codes for discrete symmetric channels based on the packing and covering properties of generalized spheres whose shape is tilted using an auxiliary probability measure. This notion generalizes previous definitions of perfect and quasi-perfect codes and encompasses maximum distance separable codes. The error probability of these codes, whenever they exist, is shown to coincide with the estimate provided by the meta-converse lower bound. We illustrate how the proposed definition naturally extends to cover almost-lossless source-channel coding and lossy compression.

关键词： Shannon theory perfect codes quasi-perfect codes maximum likelihood decoding finite blocklength analysis meta-converse hypothesis testing channel coding joint source-channel coding rate distortion theory

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source Broadcasting and Asymmetric Data Transmission With Bandwidth Expansion

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IEEE TRANSACTIONS ON COMMUNICATIONS 2019年第10期67卷 6698-6710页

作者： Bross, Shraga, I Zalach, Hagai Bar Ilan Univ Fac Engn IL-52900 Ramat Gan Israel CEVA DSP IL-4673302 Herzliyya Israel

We consider the broadcasting of a scalar memoryless Gaussian source over a two-user Gaussian broadcast channel with bandwidth expansion. In concurrent with the source description, a message that should be decoded reliably just by the "higher quality" user is sent. Conditioned on the message rate, we derive a necessary condition for the achievability of a mean-squared-error distortion pair at the two receivers, which extends the Reznic-Feder-Zamir bound. This necessary condition and a sufficient condition that we derive establish the set of achievable energy-distortion exponents for this setting.

关键词： Gaussian broadcast channel source broadcasting asymmetric data transmission joint source-channel coding

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Deep-Learning-Aided Wireless Video Transmission 23

Deep-Learning-Aided Wireless Video Transmission

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23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC)

作者： Tung, Tze-Yang Gunduz, Deniz Imperial Coll London Informat Proc & Commun Lab IPC Lab London England Univ Modena & Reggio Emilia Enzo Ferrari Dept Engn Modena Italy

ISBN: (纸本)9781665494557

We present DeepWiVe, the first-ever end-to-end joint source-channel coding (JSCC) video transmission scheme that leverages the power of deep neural networks (DNNs) to directly map video signals to channel symbols, combining video compression, channel coding, and modulation steps into a single neural transform. Our DNN decoder predicts residuals without distortion feedback, which improves video quality by accounting for occlusion/disocclusion and camera movements. We simultaneously train different bandwidth allocation networks for the frames to allow variable bandwidth transmission. Then, we train a bandwidth allocation network using reinforcement learning (RL) that optimizes the allocation of limited available channel bandwidth among video frames to maximize overall visual quality. Our results show that DeepWiVe can overcome the cliffeffect, which is prevalent in conventional separation-based digital communication schemes, and achieve graceful degradation with the mismatch between the estimated and actual channel qualities. DeepWiVe outperforms H.264 video compression followed by lowdensity parity check (LDPC) codes in all channel conditions by up to 0.0485 on average in terms of the multi-scale structural similarity index measure (MS-SSIM).

关键词： joint source-channel coding wireless video transmission deep learning reinforcement learning

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Empirical Coordination with channel Feedback and Strictly Causal or Causal Encoding

Empirical Coordination with Channel Feedback and Strictly Ca...

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IEEE International Symposium on Information Theory (ISIT)

作者： Le Treust, Mael Univ Cergy Pontoise CNRS ENSEA ETISUMR 8051 6 Ave Ponceau F-95014 Cergy Pontoise France

ISBN: (纸本)9781467377041

In multi-terminal networks, feedback increases the capacity region and helps communication devices to coordinate. In this article, we deepen the relationship between coordination and feedback by considering a point-to-point scenario with an information source and a noisy channel. Empirical coordination is achievable if the encoder and the decoder can implement sequences of symbols that are jointly typical for a target probability distribution. We investigate the impact of feedback when the encoder has strictly causal or causal observation of the source symbols. For both cases, we characterize the optimal information constraints and we show that feedback improves coordination possibilities. Surprisingly, feedback also reduces the number of auxiliary random variables and simplifies the information constraints. For empirical coordination with strictly causal encoding and feedback, the information constraint does not involve auxiliary random variable anymore.

关键词： Shannon Theory Feedback Empirical Coordination joint source-channel coding Empirical Distribution of Symbols Strictly Causal and Causal Encoding

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Lower bounds on the existence of binary error-correcting variable-length codes

Lower bounds on the existence of binary error-correcting var...

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IEEE Information Theory Workshop

作者： Lamy, C Bergot, FX THALES Commun France Gennevilliers France

ISBN: (纸本)0780377990

This paper deals with codes that combine source and channel encoding operations. After discussing the potential usefulness of these variable-length error correcting (VLEC) codes, necessary conditions on their length distribution are established. It is shown that, depending on the targetted application, several families of VLEC codes can be defined, whose conditions of existence differ.

关键词： variable-length error-correcting codes variable-length codes error correction coding joint source-channel coding bounding methods

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Contrastive Learning based Semantic Communication for Wireless Image Transmission 98

Contrastive Learning based Semantic Communication for Wirele...

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98th IEEE Vehicular Technology Conference (VTC-Fall)

作者： Tang, Shunpu Yang, Qianqian Fan, Lisheng Lei, Xianfu Deng, Yansha Nallanathan, Arumugam Zhejiang Univ Key Lab Collaborat Sensing & Autonomous Unmanned Hangzhou Peoples R China Guangzhou Univ Sch Comp Sci & Cyber Engn Guangzhou Peoples R China Southwest Jiaotong Univ Inst Mobile Commun Chengdu Peoples R China Kings Coll London Dept Engn London England Queen Mary Univ London Sch Elect Engn & Comp Sci London England

ISBN: (纸本)9798350329285

Recently, semantic communication has been widely applied in wireless image transmission systems as it can prioritize the preservation of meaningful semantic information in images over the accuracy of transmitted symbols, leading to improved communication efficiency. However, existing semantic communication approaches still face limitations in achieving considerable inference performance in downstream AI tasks like image recognition, or balancing the inference performance with the quality of the reconstructed image at the receiver. Therefore, this paper proposes a contrastive learning (CL)-based semantic communication approach to overcome these limitations. Specifically, we regard the image corruption during transmission as a form of data augmentation in CL and leverage CL to reduce the semantic distance between the original and the corrupted reconstruction while maintaining the semantic distance among irrelevant images for better discrimination in downstream tasks. Moreover, we design a two-stage training procedure and the corresponding loss functions for jointly optimizing the semantic encoder and decoder to achieve a good trade-off between the performance of image recognition in the downstream task and reconstructed quality. Simulations are finally conducted to demonstrate the superiority of the proposed method over the competitive approaches. In particular, the proposed method can achieve up to 56% accuracy gain on the CIFAR10 dataset when the bandwidth compression ratio is 1/48.

关键词： Semantic communication image transmission contrastive learning joint source-channel coding

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Task-Oriented Semantic Communication with Foundation Models

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China Communications 2024年第7期21卷 65-77页

作者： Chen Mingkai Liu Minghao Zhang Zhe Xu Zhiping Wang Lei Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of EducationNanjing University of Posts and TelecommunicationsNanjing 210003China School of Ocean Information Engineering Jimei UniversityXiamen 361021China Key Laboratory of Underwater Acoustic Communication and Marine Information Technology(Xiamen University) Ministry EducationXiamen 361005China

In the future development direction of the sixth generation(6G)mobile communication,several communication models are proposed to face the growing challenges of the *** rapid development of artificial intelligence(AI)foundation models provides significant support for efficient and intelligent communication *** this paper,we propose an innovative semantic communication paradigm called task-oriented semantic communication system with foundation ***,we segment the image by using task prompts based on the segment anything model(SAM)and contrastive language-image pretraining(CLIP).Meanwhile,we adopt Bezier curve to enhance the mask to improve the segmentation ***,we have differentiated semantic compression and transmission approaches for segmented ***,we fuse different semantic information based on the conditional diffusion model to generate high-quality images that satisfy the users'specific task ***,the experimental results show that the proposed system compresses the semantic information effectively and improves the robustness of semantic communication.

关键词： diffusion model foundation model joint source-channel coding task-oriented semantic communication

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joint resource allocation for MIMO-OFDM video transmission systems with unequal error protection

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Journal of Harbin Institute of Technology(New Series) 2012年第2期19卷 119-124页

作者：张成文刘鑫谭学治 Communication Research Center Harbin Institute of Technology

To improve the performance of MIMO-OFDM video transmission systems on the limitation of wireless bandwidth and transmitting power,we propose an adaptive joint resource allocation algorithm with unequal error protection(UEP) based on joint source-channel coding(JSCC) according to H.264 video compression standard and RCPT channel *** to different thresholds of the average SNR of subchannels,the algorithm dynamically allocates the source coding parameters of original video data and the channel coding parameters of RCPT,which realizes UEP for the compressed video data of different *** the bit and power allocation based on MQAM modulation and the subspace allocation based on beamforming technology for different subcarriers,an adaptive joint resource allocation making full use of space-frequency domain resources have been *** simulation results indicate that the algorithm improves the adaptability of video transmission systems in different wireless environments and the quality of video retrieval.

关键词： video transmission MIMO-OFDM unequal error protection joint source-channel coding

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On Asymptotic Analysis of Energy-Distortion Tradeoff for Low-Delay Transmission Over Gaussian channels

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IEEE TRANSACTIONS ON COMMUNICATIONS 2021年第7期69卷 4448-4460页

作者： Sevinc, Ceren Tuncel, Ertem Univ Calif Riverside Dept Elect & Comp Engn Riverside CA 92521 USA

Asymptotic energy-distortion performance of zero- and low-delay transmission of Gaussian sources over energy-limited Gaussian channels is studied. A lower bound for the leading term in the negative logarithm of the distortion, termed the energy-distortion exponent, is derived through an achievable scheme based on high-resolution quantization coupled with orthogonal signaling. The higher-order term in the negative logarithm of the distortion, termed the energy-distortion dispersion, is optimized while keeping the leading term, the energy-distortion exponent, at its optimal (respectively, the best known) value for the zero-delay (respectively, low-delay) regime. In contrast with the decaying dispersion previously reported in the literature, the proposed coding scheme achieves a constant dispersion. When the scheme is optimized, this constant can be improved with respect to its naive value, i.e., that achieved by optimizing purely the source coding performance instead of the end-to-end distortion. Lastly, a tradeoff of achievable energy-distortion exponents is derived for broadcast scenarios by extending the point-to-point scheme to include a successive refinement source coder coupled with two rounds of orthogonal signaling. A simple parametric computation algorithm is derived for the tradeoff.

关键词： Broadcast channels energy-distortion exponent energy-distortion tradeoff high-resolution quantization theory joint source-channel coding low-delay orthogonal signaling zero-delay

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