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检索条件"主题词=Joint Source-channel coding"

共 624 条记录，以下是101-110 订阅

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Distributed joint source-channel coding for Functions over a Multiple Access channel

Distributed Joint Source-Channel Coding for Functions over a...

引用

IEEE Global Telecommunications Conference (GLOBECOM 09)

作者： Rajesh, R. Sharma, Vinod Indian Inst Sci Dept Elect Commun Engg Bangalore 560012 Karnataka India

ISBN: (纸本)9781424441471

In this paper we provide sufficient conditions for lossy transmission of functions of correlated data over a multiple access channel (MAC). The conditions obtained can be shown as generalized version of Yamamoto's result [28]. We also obtain efficient joint source-channel coding schemes for transmission of discrete and continuous alphabet sources to recover the function values.

关键词： joint source-channel coding Graph coloring Lipschitz functions Correlated sources

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Spatially Coupled LDPC Codes Based joint source-channel coding 5th

Spatially Coupled LDPC Codes Based Joint Source-Channel Codi...

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5th International Conference on Wireless Communications and Applications (ICWCA)

作者： Lian Qiufang Lin, Zhou Chen Qiwang Chen, Chen Xi, Wang Natl Huaqiao Univ Coll Informat Sci & Engn Xiamen Key Lab Mobile Multimedia Commun Xiamen 361021 Fujian Peoples R China China Mobile Commun Grp Fujian Co Ltd Fuzhou 350003 Fujian Peoples R China

ISBN: (纸本)9789811922558;9789811922541

source coding and channel coding are the hot research parts in information theory. The source channel separation system cannot take full advantage of the correlation between source and channel. The performance of the joint source-channel coding (JSCC) system can be improved by using the redundant information of the source and this system is more suitable for future continuous error-free communication needs. In recent years, many applications require error-free transmission with low latency. Due to the special structure of parity check matrices (PCM), spatially coupled low-density parity-check (SC-LDPC) codes can adopt the sliding window decoding (SWD) algorithm to have the characteristics of low delay and ensure continuous error-free transmission in streaming media applications. Simulation results show that both spreading factor and window size affect decoding performance. This paper reviews the design of the sliding-window decoding algorithm in additive white Gaussian noise (AWGN) channel based on SC-LDPC codes and prospects future work.

关键词： joint source-channel coding Sliding window decoding Spatially coupled low-density parity-check codes

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DEEP joint source-channel coding FOR WIRELESS IMAGE RETRIEVAL

DEEP JOINT SOURCE-CHANNEL CODING FOR WIRELESS IMAGE RETRIEVA...

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Jankowski, Mikolaj Gunduz, Deniz Mikolajczyk, Krystian Imperial Coll London London England

ISBN: (纸本)9781509066315

Motivated by surveillance applications with wireless cameras or drones, we consider the problem of image retrieval over a wireless channel. Conventional systems apply lossy compression on query images to reduce the data that must be transmitted over a bandwidth and power limited wireless link. We first note that reconstructing the original image is not needed for retrieval tasks;hence, we introduce a deep neutral network (DNN) based compression scheme targeting the retrieval task. Then, we completely remove the compression step, and propose another DNN-based communication scheme that directly maps the feature vectors to channel inputs. This joint source-channel coding (JSCC) approach not only improves the end-to-end accuracy, but also simplifies and speeds up the encoding operation which is highly beneficial for power and latency constrained IoT applications.

关键词： joint source-channel coding retrieval person re-identification IoT deep learning

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Optimal joint source-channel coding using unequal error protection for the scalable extension of H.264/MPEG-4 AVC

Optimal joint source-channel coding using unequal error prot...

引用

IEEE International Conference on Image Processing (ICIP 2007)

作者： Stoufs, M. Munteanu, A. Schelkens, P. Cornelis, J. Vrije Univ Brussel Dept Elect & Informat Interdisciplinary Inst Broadband Technol B-1050 Brussels Belgium

ISBN: (纸本)9781424414369

This paper proposes an optimized joint source-channel coding methodology with unequal error protection for the transmission of video encoded with the recently developed scalable extension of H.264/MPEG-4 AVC. The proposed methodology uses a simplified Viterbi-based search method which significantly outperforms the classical exhaustive search method in terms of computational complexity, leading to a practically applicable solution at the expense of a minimal loss of optimality. Experimental results show the effectiveness of our protection methodology and illustrate its capability to provide graceful degradation in the presence of channel mismatches.

关键词： scalable video coding error resilience joint source-channel coding unequal error protection

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Deep joint source-channel coding for Wireless Image Transmission with Semantic Importance 96

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

引用

IEEE 96th Vehicular Technology Conference (VTC-Fall)

作者： Sun, Qizheng Guo, Caili Yang, Yang Chen, Jiujiu Tang, Rui Liu, Chuanhong Beijing Univ Posts & Telecommun Beijing Key Lab Network Syst Architecture & Conve Beijing Lab Adv Informat Networks Beijing 100876 Peoples R China

ISBN: (纸本)9781665454681

The sixth-generation mobile communication system proposes the vision of smart interconnection of everything, which requires accomplishing communication tasks while ensuring the performance of intelligent tasks. A joint source-channel coding method based on semantic importance is proposed, which aims at preserving semantic information during wireless image transmission and thereby boosting the performance of intelligent tasks for images at the receiver. Specifically, we first propose semantic importance weight calculation method, which is based on the gradient of intelligent task's perception results with respect to the features. Then, we design the semantic loss function in the way of using semantic weights to weight the features. Finally, we train the deep joint source-channel coding network using the semantic loss function. Experiment results demonstrate that the proposed method achieves up to 57.7% and 9.1% improvement in terms of intelligent task's performance compared with the source-channel separation coding method and the deep source-channel joint coding method without considering semantics at the same compression rate and signal-to-noise ratio, respectively.

关键词： joint source-channel coding semantic importance semantic preservation semantic loss function intelligent task perception results

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Deep Learning-Based Adaptive joint source-channel coding using Hypernetworks

Deep Learning-Based Adaptive Joint Source-Channel Coding usi...

引用

IEEE International Mediterranean Conference on Communications and Networking (IEEE MeditCom)

作者： Xie, Songjie He, Hengtao Li, Hongru Song, Shenghui Zhang, Jun Zhang, Ying-Jun Angela Letaief, Khaled B. Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Peoples R China Chinese Univ Hong Kong Dept Informat Engn Hong Kong Peoples R China

ISBN: (纸本)9798350309492;9798350309485

Deep learning-based joint source-channel coding (DJSCC) is expected to be a key technique for the next-generation wireless networks. However, the existing DJSCC schemes still face the challenge of channel adaptability as they are typically trained under specific channel conditions. In this paper, we propose a generic framework for channel-adaptive DJSCC by utilizing hypernetworks. To tailor the hypernetwork-based framework for communication systems, we propose a memory-efficient hypernetwork parameterization and then develop a channel-adaptive DJSCC network, named Hyper-AJSCC. Compared with existing adaptive DJSCC based on the attention mechanism, HyperAJSCC introduces much fewer parameters and can be seamlessly combined with various existing DJSCC networks without any substantial modifications to their neural network architecture. Extensive experiments demonstrate the better adaptability to channel conditions and higher memory efficiency of HyperAJSCC compared with state-of-the-art baselines.

关键词： joint source-channel coding deep learning deep neural network hypernetworks

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MULTIPLE DESCRIPTION ANALOG joint source-channel coding FOR PARALLEL channelS WITH SIDE INFORMATION

MULTIPLE DESCRIPTION ANALOG JOINT SOURCE-CHANNEL CODING FOR ...

引用

20th European Signal Processing Conference (EUSIPCO)

作者： Alustiza, Iker Erdozain, Aitor Crespo, Pedro Beferull-Lozano, Baltasar Un Navarra Tecnun Manuel de Lardizabal 15 San Sebastian 20018 Spain Univ Valencia Paterna Inst Robot Tecnol Informac & Commun Valencia 46980 Spain

ISBN: (纸本)9781467310680

With the purpose of reducing the coding complexity and delay of the separation-based schemes, an analog joint source-channel coding scheme is proposed for transmissions through parallel AWGN channels with side information at the receiver. This scheme divides the bidimensional source space into a set of hexagons and transmits the relative position of the source vectors inside the corresponding hexagon by using two complimentary analog mappings. The results are satisfactory, specially taking into consideration the low complexity and delay of the proposed scheme.

关键词： joint source-channel coding analog mappings side information multiple description coding

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Distributed Deep joint source-channel coding over a Multiple Access channel

Distributed Deep Joint Source-Channel Coding over a Multiple...

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IEEE International Conference on Communications (IEEE ICC)

作者： Yilmaz, Selim F. Karamanli, Can Gunduz, Deniz Imperial Coll London Dept Elect & Elect Engn London England

ISBN: (纸本)9781538674628

We consider distributed image transmission over a noisy multiple access channel (MAC) using deep joint source-channel coding (DeepJSCC). It is known that Shannon's separation theorem holds when transmitting independent sources over a MAC in the asymptotic infinite block length regime. However, we are interested in the practical finite block length regime, in which case separate source and channel coding is known to be suboptimal. We introduce a novel joint image compression and transmission scheme, where the devices send their compressed image representations in a non-orthogonal manner. While non-orthogonal multiple access (NOMA) is known to achieve the capacity region, to the best of our knowledge, non-orthogonal joint source-channel coding (JSCC) scheme for practical systems has not been studied before. Through extensive experiments, we show significant improvements in terms of the quality of the reconstructed images compared to orthogonal transmission employing current DeepJSCC approaches particularly for low bandwidth ratios. We publicly share source code to facilitate further research and reproducibility.

关键词： joint source-channel coding non-orthogonal multiple access wireless image transmission deep learning

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Impact of Quantization Noise on CNN-based joint source-channel coding and Modulation 20

Impact of Quantization Noise on CNN-based Joint Source-Chann...

引用

IEEE 20th Consumer Communications and Networking Conference (CCNC)

作者： Matsumoto, Keigo Inoue, Yoshiaki Hara-Azumi, Yuko Maruta, Kazuki Nakayama, Yu Hisano, Daisuke Osaka Univ Grad Sch Engn Osaka Japan Tokyo Inst Technol Sch Engn Tokyo Japan Tokyo Univ Sci Grad Sch Engn Tokyo Japan Tokyo Univ Agr & Technol Inst Engn Tokyo Japan

ISBN: (纸本)9781665497343

This paper investigated the impact of a quantizer in analog-to-digital and digital-to-analog converters in communication devices on image quality when using deep learning-based joint source-channel coding modulation (JSCCM) for image transmission. In recent years, JSCCM, which efficiently encodes images and videos with low information entropy, has attracted great attention. JSCCM has a structure based on an autoencoder and determines the compression ratios for the image input by adjusting the number of IQ symbol output. The IQ symbol output from the encoder are allocated to symbol constellations with higher degrees of arbitrariness than those in typical square quadrature amplitude modulation and are therefore expected to be strongly affected by the quantization noise. In this paper, we employed quantization to the IQ symbol sequence and investigated its effect. Adjusting the quantizer's clipping ratio and the number of quantization bits, we examined the images' tolerance of the peak signal-to-noise ratio (PSNR). The simulation results showed that by adequately adjusting the clipping ratio, the image quality can be guaranteed to be equivalent to ideal conditions without quantization noise, and the number of required quantization bits that do not degrade the PSNR, was calculated.

关键词： deep learning image coding joint source-channel coding quantization

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Minimizing End-to-End Latency for joint source-channel coding Systems 59

Minimizing End-to-End Latency for Joint Source-Channel Codin...

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59th Annual IEEE International Conference on Communications (IEEE ICC)

作者： Chi, Kaiyi Yang, Qianqian Shu, Yuanchao Yang, Zhaohui Shi, Zhiguo Zhejiang Univ Coll Control Sci & Engn Hangzhou 310027 Peoples R China Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China

ISBN: (纸本)9798350304060;9798350304053

While existing studies have highlighted the advantages of deep learning (DL)-based joint source-channel coding (JSCC) schemes in enhancing transmission efficiency, they often overlook the crucial aspect of resource management during the deployment phase. In this paper, we propose a resource management approach to minimize the transmission latency in an uplink JSCC-based system. We first analyze the correlation between end-to-end latency and task performance, based on which the end-to-end delay model for each device is established. Then, we formulate a non-convex optimization problem aiming at minimizing the maximum end-to-end latency across all devices, which is proved to be NP-hard. We then transform the original problem into a more tractable one, from which we derive the closed form solution on the optimal compression ratio, truncation threshold selection policy, and resource allocation strategy. We further introduce a heuristic algorithm with low complexity, leveraging insights from the structure of the optimal solution. Simulation results demonstrate that both the proposed optimal algorithm and the heuristic algorithm significantly reduce end-to-end latency. Notably, the proposed heuristic algorithm achieves nearly the same performance to the optimal solution but with considerably lower computational complexity.

关键词： Semantic communication joint source-channel coding resource allocation latency optimization

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