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检索条件"主题词=Joint Source-channel coding"

共 624 条记录，以下是111-120 订阅

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Distributed Deep joint source-channel coding with Decoder-Only Side Information 1

Distributed Deep Joint Source-Channel Coding with Decoder-On...

引用

1st IEEE International Conference on Machine Learning for Communication and Networking (IEEE ICMLCN)

作者： Yilmaz, Selim F. Ozyilkan, Ezgi Gunduz, Deniz Erkip, Elza Imperial Coll London Dept Elect & Elect Engn London England New York Univ Dept Elect & Comp Engn New York NY USA

ISBN: (纸本)9798350343205;9798350343199

We consider low-latency image transmission over a noisy wireless channel when correlated side information is present only at the receiver side (the Wyner-Ziv scenario). In particular, we are interested in developing practical schemes using a data-driven joint source-channel coding (JSCC) approach, which has been previously shown to outperform conventional separation-based approaches in the practical finite blocklength regimes, and to provide graceful degradation with channel quality. We propose a novel neural network architecture that incorporates the decoder-only side information at multiple stages at the receiver side. Our results demonstrate that the proposed method succeeds in integrating the side information, yielding improved performance at all channel conditions in terms of the various quality measures considered here, especially at low channel signal-to-noise ratios (SNRs) and small bandwidth ratios (BRs). We have made the source code of the proposed method public to enable further research, and the reproducibility of the results.

关键词： joint source-channel coding Wyner-Ziv coding wireless image transmission deep learning multi-view learning

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LDPC-based joint, source-channel coding scheme for multimedia communications 8

LDPC-based joint, source-channel coding scheme for multimedi...

引用

8th International Conference on Communication Systems

作者： Yin, LG Lu, JH Wu, YS Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

ISBN: (纸本)0780375106

joint source-channel coding schemes have been proven to be effective ways for reliable multimedia communications. In this paper, we develop a joint source-channel coding scheme that well combines the hidden Markov source (HMS) estimation and the powerful low-density parity-check (LDPC) codes with an iterative estimation/decoding scheme. With this coding method, the source redundancy could be accurately extracted by the hidden Markov estimation without using any priori information about the source. Moreover, the interleaver that is likely used to separate the source coding and channel coding is exempted by exploiting the randomizing property of the LDPC codes, while the channel decoding procedure may be implemented in parallel, resulting in good performance with a fairly low decoding complexity and delay. Simulation results have shown that the proposed scheme may achieve a much better performance than that of the standard coding scheme over the binary input additive white Gaussian noise (BIAWGN) channels.

关键词： joint source-channel coding hidden Markov source (HMS) estimation low density parity check (LDPC) codes iterative decoding multimedia communications

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VAE for joint source-channel coding of Distributed Gaussian sources over AWGN MAC 21

VAE for Joint Source-Channel Coding of Distributed Gaussian ...

引用

21st IEEE International Workshop on Signal Processing Advances in Wireless Communications (IEEE SPAWC)

作者： Saidutla, Yashas Malur Abdi, Afshin Fekri, Faramarz Georgia Inst Technol Sch ECE Atlanta GA 30332 USA

ISBN: (纸本)9781728154787

In this paper, we introduce a framework for joint source-channel coding of distributed Gaussian sources over a multiple access AWGN channel. Although there are prior works that have studied this, they either strongly rely on intuition to design encoders and decoder or require the knowledge of the complete joint distribution of all the distributed sources. Our system overcomes this. We model our system as a Variational Autoencoder and leverage insight provided by this connection to propose a crucial regularization mechanism for learning. This allows us to beat the state of the art by improving the signal reconstruction quality by almost 1dB for certain configurations. The end-to-end learned system is also found to be robust to channel condition variations of +/- 5dB and shows a drop in signal reconstruction quality by at most 1dB. Finally, we propose a novel lower bound on the optimal distortion in signal reconstruction and empirically showcase the tightness of the bound in comparison with the existing bound.

关键词： joint source-channel coding distributed encoding multiple access channels machine learning deep learning

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Optimal Power Allocation and joint source-channel coding for Wireless DS-CDMA Visual Sensor Networks

Optimal Power Allocation and Joint Source-Channel Coding for...

引用

Conference on Visual Information Processing and Communication II

作者： Pandremmenou, Katerina Kondi, Lisimachos P. Parsopoulos, Konstantinos E. Univ Ioannina Dept Comp Sci GR-45110 Ioannina Greece

ISBN: (纸本)9780819484192

In this paper, we propose a scheme for the optimal allocation of power, source coding rate, and channel coding rate for each of the nodes of a wireless Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network. The optimization is quality-driven, i.e. the received quality of the video that is transmitted by the nodes is optimized. The scheme takes into account the fact that the sensor nodes may be imaging scenes with varying levels of motion. Nodes that image low-motion scenes will require a lower source coding rate, so they will be able to allocate a greater portion of the total available bit rate to channel coding. Stronger channel coding will mean that such nodes will be able to transmit at lower power. This will both increase battery life and reduce interference to other nodes. Two optimization criteria are considered. One that minimizes the average video distortion of the nodes and one that minimizes the maximum distortion among the nodes. The transmission powers are allowed to take continuous values, whereas the source and channel coding rates can assume only discrete values. Thus, the resulting optimization problem lies in the field of mixed-integer optimization tasks and is solved using Particle Swarm Optimization. Our experimental results show the importance of considering the characteristics of the video sequences when determining the transmission power, source coding rate and channel coding rate for the nodes of the visual sensor network.

关键词： Visual sensor networks DS-CDMA Cross-layer optimization Resource allocation joint source-channel coding H.264 Rate compatible punctured convolutional codes Particle Swarm Optimization

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A Robust Blind Watermarking Scheme Based on Attention Mechanism and Neural joint source-channel coding 24

A Robust Blind Watermarking Scheme Based on Attention Mechan...

引用

IEEE 24th International Workshop on Multimedia Signal Processing (MMSP)

作者： Mei, Yuting Wu, Guanzhong Yu, Xiangyu Liu, Beibei South China Univ Technol Sch Elect & Informat Engn Guangzhou Peoples R China

ISBN: (数字)9781665471893

ISBN: (纸本)9781665471893

Due to the importance of protecting digital images in the modern world, digital image watermarking draws the attention of academia because of its applications in proving the authenticity and integrity of digital images. The performance of current watermarking algorithms needs to be improved to cope with the growing demand for better imperceptibility, greater robustness, and larger capacity. In response to the above requirements, a new robust blind watermarking algorithm is proposed in this paper, which mainly utilizes convolutional neural networks to embed watermarks in DCT domain. An attention module is introduced to calculate the confidence that each image pixel block contains watermark information, thus making our algorithm robust enough to deal with Crop attack. In addition, the introduction of a learning based solution for joint source and channel coding enables our algorithm to take grayscale images with simple backgrounds as input watermarks while maintaining great imperceptibility and robustness. Extensive experiments demonstrate the superiority of our algorithm.

关键词： Blind watermarking Convolutional neural network Attention mechanism joint source-channel coding

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INFLATING COMPRESSED SAMPLES: A joint source-channel coding APPROACH FOR NOISE-RESISTANT COMPRESSED SENSING

INFLATING COMPRESSED SAMPLES: A JOINT SOURCE-CHANNEL CODING ...

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： HesamMohseni, A. Babaie-Zadeh, M. Jutten, C. Sharif Univ Technol Dept Elect Engn Tehran Iran GIPSA LAB Grenoble France

ISBN: (纸本)9781424423538

Recently, a lot of research has been done on compressed sensing, capturing compressible signals using random linear projections to a space of radically lower dimension than the ambient dimension of the signal. The main impetus of this is that the radically dimension-lowering linear projection step can be done totally in analog hardware, in some cases even in constant time, to avoid the bottleneck in sensing and quantization steps where a large number of samples need to be sensed and quantized in short order, mandating the use of it large number of fast expensive sensors and A/D converters. Reconstruction algorithms from these projections have been found that come within distortion levels comparable to the state of the art in lossy compression algorithms. This paper considers a variation on compressed sensing that makes it resistant to spiky noise. This is achieved by an analog real-field error-correction coding step. It results in a small asymptotic overhead in the number of samples, but makes exact reconstruction under spiky measurement noise, one type of which is the salt and pepper noise in imaging devices, possible. Simulations are per-formed that corroborate our claim and in fact substantially improve reconstruction under unreliable sensing characteristics and are stable even under small perturbations with Gaussian noise.

关键词： Compressed Sensing joint source-channel coding Sparse solution problems Natural Images Error-Correcting codes

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Bounds for joint source-channel coding at High SNR

Bounds for Joint Source-Channel Coding at High SNR

引用

IEEE International Symposium on Information Theory (ISIT)

作者： Tridenski, Sergey Zamir, Ram Tel Aviv Univ Dept EE Syst IL-69978 Tel Aviv Israel

ISBN: (纸本)9781457705953

Shannon's capacity and rate-distortion function, combined with the separation principle, provide tight bounds for the minimum possible distortion in joint source-channel coding. These bounds, however, are usually achievable only in the limit of large block length. In their 1973 paper, Ziv and Zakai provide a family of alternative capacity and rate-distortion functions, based on functionals satisfying the data-processing inequality, which potentially give tighter bounds for systems with a small block length, e.g., for scalar modulation. We examine a recently proposed approximation for the Ziv-Zakai bounds based on the Renyi-divergence functional. For the specific case of a uniform source, we derive explicit bounds on the Ziv-Zakai-Renyi rate-distortion function, which prove this approximation in the limit of small distortion. Our results can be extended, using the same technique, to more general sources.

关键词： Encoding joints Mutual information ReÌnyi-divergence functional Resource description framework Shannon's capacity Signal to noise ratio Ziv-Zakai bound approximation Ziv-Zakai-ReÌnyi rate- distortion function approximation theory capacity function combined source-channel coding data-processing inequality joint source-channel coding rate distortion theory rate-distortion function scalar modulation separation principle

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Low-Delay Analog Distributed joint source-channel coding using SIRENs 29

Low-Delay Analog Distributed Joint Source-Channel Coding usi...

引用

29th European Signal Processing Conference (EUSIPCO)

作者： Xuan, Ziwei Narayanan, Krishna Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA

ISBN: (纸本)9789082797060

We consider the design of joint source-channel coding (JSCC) schemes for two multiterminal source-channel coding problems - namely, the transmission of a Gaussian source with side information at the receiver and the transmission of bivariate Gaussian sources over two independent Gaussian channels. Our focus is on low-delay transmission. We formulate the design problem as optimization of an autoencoder (AE) model, and show that sinusoidal representation networks (SIRENs) are a good choice due to their inherent periodicity and the ability of stretched sinusiods to cover the source space. We show that SIRENs outperform parametric ReLU based networks. The complexity of the proposed method scales better with source dimension than the best traditional schemes known in the literature while their performance is comparable to or better than that of the best traditional schemes. We demonstrate that the spontaneously learned encoder mappings share resemblance to the classical Wyner-Ziv mappings for JSCC with side information, and exhibits structured patterns in the case of distributed coding that are interpretable.

关键词： Distributed source-channel coding joint source-channel coding SIRENs deep learning

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Prior Model-based Deep joint source-channel coding for Wireless Image Transmission over Multipath Fading channels

Prior Model-based Deep Joint Source-Channel Coding for Wirel...

引用

IEEE/CIC International Conference on Communications in China (ICCC)

作者： Wang, Feng Chen, Xuechen Deng, Xiaoheng Cent South Univ Sch Comp Sci & Engn Changsha Peoples R China Cent South Univ Sch Elect Informat Changsha Peoples R China

ISBN: (纸本)9798350378412

Deep joint source channel coding (DeepJSCC) achieves remarkable results in wireless image transmission. However, image transmission under multipath fading channels based on DeepJSCC is still a huge challenge. Therefore, we propose a subchannel matching strategy based on prior model and DeepJSCC over multipath fading channels. According to channel state information (CSI), our scheme maps the more important image features obtained from the prior model to higher quality subchannels. In practice, the resources can be fully utilized according to the acquired CSI, resulting in higher image transmission quality. Extensive experiments show that our approach achieves state-of-the-art performance and channel resilience over multipath fading channels compared to existing DeepJSCC schemes. In addition, our scheme has good channel adaptability and does not suffer from the cliff effect in the case of channel signal-to-noise ratio (CSNR) of additive Gaussian white noise (AWGN) mismatch.

关键词： Prior model subchannel matching joint source-channel coding

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H.263+packet video over wireless IP networks using rate-compatible punctured turbo (RCPT) codes with joint source-channel coding

H.263+packet video over wireless IP networks using rate-comp...

引用

IEEE International Conference on Image Processing

作者： Pei, Y Modestino, JW Rensselaer Polytech Inst ECSE Dept Troy NY 12180 USA

ISBN: (纸本)0780376226

In this paper, we consider real-time video coding and transmission over packet-switched wireless IP networks using RCPT codes in a joint source and channel coding (JSCC) approach. In particular, the performance of this JSCC approach employing RCPT coding schemes for RTP-H.263+ packet video transmission over so fading Rician channels is studied. Results indicate that an RCPT-JSCC approach is attractive for real-time video applications an leads to increased system capacity together with more acceptable delivered video quality over time-varying wireless networks.

关键词： video transmission RTP-H.263+ RCPT codes joint source-channel coding Rician fading passive error recovery

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