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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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joint source-channel Bit Allocation Based on Expected End-to-End Distortion Model

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Journal of Donghua University(English Edition) 2010年第4期27卷 458-462页

作者：马汉杰陈耀武 Institute of Advanced Digital Technology and Instrumentation Zhejiang University

An adaptive joint source channel bit allocation method for video communications over error-prone channel is *** protect the bit-streams from the channel bit errors,the rate compatible punctured convolution(RCPC)code is used to produce coding rates varying from 4/5 to 1/2 using the same encoder and the Viterbi *** expected end-to-end distortion model was presented to estimate the distortion introduced in compressed source coding due to quantization and channel bit errors *** on the proposed end-to-end distortion model,an adaptive joint source-channel bit allocation method was proposed under time-varying error-prone channel *** results show that the proposed methods could utilize the available channel capacity more efficiently and achieve better video quality than the other fixed coding-based bit allocation methods when transmitting over error-prone channels.

关键词： joint source-channel coding end-to-end distortion bit allocation rate compatible punctured convolution code

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Distortion Exponent in MIMO Fading channels With Time-Varying source Side Information

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IEEE TRANSACTIONS ON INFORMATION THEORY 2016年第6期62卷 3597-3617页

作者： Aguerri, Inaki Estella Gunduz, Deniz Imperial Coll London Dept Elect & Elect Engn London SW7 2BT England Huawei Technol Co Ltd France Res Ctr Math & Algorithm Sci Lab F-92100 Boulogne France Imperial Coll London Dept Elect & Elect Engn London SW7 2BT England

Transmission of a Gaussian source over a time-varying multiple-input multiple-output (MIMO) channel is studied under strict delay constraints. Availability of a correlated side information at the receiver is assumed, whose quality, i.e., its correlation with the source signal, also varies over time. A block-fading model is considered for the states of the time-varying channel and side information;perfect state information at the receiver is assumed, while the transmitter knows only the statistics. The high signal to noise ratio performance, characterized by the distortion exponent, is studied for this joint source-channel coding problem. An upper bound is derived and compared with several lower bounds based on list decoding (LD), hybrid digital-analog transmission, as well as multi-layer schemes, which transmit successive refinements of the source, relying on progressive or superposition transmission with LD. The optimal distortion exponent is characterized for the single-input multiple-output and multiple-input single-output scenarios by showing that the distortion exponent achieved by multi-layer superposition encoding with joint decoding meets the proposed upper bound. In the MIMO scenario, the optimal distortion exponent is characterized in the low bandwidth ratio regime, and it is shown that the multi-layer superposition encoding performs very close to the upper bound in the high bandwidth ratio regime.

关键词： Distortion exponent joint source-channel coding time-varying channel and side information list decoding broadcast codes successive refinement

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Compressed-and-Forward: Compressive Sensing for Cooperative Communication

Compressed-and-Forward: Compressive Sensing for Cooperative ...

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IEEE International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS)

作者： Yeh, Chia-Hung Lin, Yu-Liang Liu, Cheng-Chih Huang, Wan-Jen Natl Sun Yat Sen Univ Dept Elect Engn Kaohsiung Taiwan Natl Sun Yat Sen Univ Inst Communicat Engn Kaohsiung Taiwan

ISBN: (纸本)9781467350839;9781467350815

Cooperative communication has been shown that it is an effective way to achieve spatial diversity in order to combat the user-outage caused by effects fading channel. Except for amplify-and-forward (AF) and decode-and-forward (DF), compressed-and-forward (CF) is also an efficient forwarding strategy. In the existing CF protocol, the relay will switch to the DF mode when the source transmitted signal can be recovered by the relay completely;however, no further compression is made in this scheme. This paper proposes a new CF scheme. The relay will estimate if the codeword in a predefined block can be succeeded decoded, then choose the corresponding forwarding methods which are based on joint source-channel coding or compressive sensing. At the decode side, a joint decoder is designed to decode the source according to the relay compression mode. Simulation results show that the proposed CF scheme can acquire the spatial diversity and outperform AF and DF schemes.

关键词： cooperative communication compressed-and-forward joint source-channel coding compressive sensing

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Low-Complexity Hybrid Transceivers for Uplink Multiuser mmWave MIMO by User Clustering 27

Low-Complexity Hybrid Transceivers for Uplink Multiuser mmWa...

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27th European Signal Processing Conference (EUSIPCO)

作者： Perez-Adan, Darian Gonzalez-Coma, Jose P. Fresnedo, Oscar Castedo, Luis Univ A Coruna Dept Comp Engn CITIC La Coruna Spain

ISBN: (纸本)9789082797039

The high cost and power consumption of millimeter wave (mmWave) radio frequency (RF) hardware elements demands for advanced signal processing techniques to design MIMO transceivers. Hybrid analog-digital architectures for MIMO transceivers have become an attractive strategy to reduce the number of RF chains of the transceivers. In the uplink of a multiuser mmWave MIMO system, this hardware reduction is limited by the number of users to be handled, which can be rather large. In this work, we propose to use distributed quantizer linear coding (DQLC) in order to superimpose correlated sources in a cluster-based uplink multiuser mmWave MIMO system and reduce the number of RF chains at the receiver. The scheduling policy to cluster the transmitters is also analyzed by considering the correlation of the sources and channel state information (CSI). Numerical results show the advantage of employing the proposed scheme to reduce hardware complexity.

关键词： Millimeter wave joint source-channel coding uplink source correlation multiuser

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Deep Learning-Based Forward-Aware Quantization for Satellite-Aided Communications via Information Bottleneck Method

Deep Learning-Based Forward-Aware Quantization for Satellite...

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joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit)

作者： Hummert, Matthias Hassanpour, Shayan Wuebben, Dirk Dekorsy, Armin Univ Bremen Dept Commun Engn D-28359 Bremen Germany

ISBN: (纸本)9798350344998;9798350345001

We consider a two-hop transmission setup in the context of Non-Terrestrial Networks (NTNs). Explicitly, a noisy source signal should be compressed at an on-ground relay node before getting forwarded over an error-prone and rate-limited channel to a satellite transponder. The impacts of this imperfect forwarding should be integrated into the compressor's design formulation. In full harmony with the Information Bottleneck (IB) principle, we choose the Mutual Information (MI) as the fidelity criterion and devise a data-driven algorithm, the Deep Forward-Aware Vector Information Bottleneck (Deep FAVIB), to tackle the design problem, when solely a finite sample set is available. To this end, first we derive a tractable objective function and, later on, utilize it to train the encoder and decoder Deep Neural Networks (DNNs) in the introduced learning architecture. Our approach here, that is based on (generative) latent variable models, extends the well-known concepts of Variational Auto-Encoders (VAEs) and Deep Variational Information Bottleneck (Deep VIB) from remote source coding to joint source-channel coding. To corroborate the effectiveness of our data-driven approach, we also present several numerical results over a typical transmission scenario for NTNs.

关键词： 6G NTN deep learning information bottleneck joint source-channel coding variational auto-encoder

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