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检索条件"主题词=Joint Source-channel coding"

共 621 条记录，以下是571-580 订阅

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A Perceptual Study of the Decoding Process of the SoftCast Wireless Video Broadcast Scheme 23

A Perceptual Study of the Decoding Process of the SoftCast W...

引用

23rd IEEE International Workshop on Multimedia Signal Processing (IEEE MMSP)

作者： Trioux, Anthony Valenzise, Giuseppe Cagnazzo, Marco Kieffer, Michel Coudoux, Francois-Xavier Corlay, Patrick Gharbi, Mohamed Univ Lille Univ Polytech Hauts de France CNRS YNCREACent LilleUMR 8520IEMNDOAE F-59313 Valenciennes France Inst Polytech Paris Telecom ParisTech LTCI Paris France Univ Paris Saclay CNRS Cent Supelec L2S F-91192 Gif Sur Yvette France

ISBN: (纸本)9781665432870

The SoftCast scheme has been proposed as a promising alternative to traditional video broadcasting systems in wireless environments. In its current form, SoftCast performs image decoding at the receiver side by using a Linear Least Square Error (LLSE) estimator. Such approach maximizes the reconstructed quality in terms of Peak Signal-to-Noise Ratio (PSNR). However, we show that the LLSE induces an annoying blur effect at low channel Signal-to-Noise Ratio (CSNR) quality. To cancel this artifact, we propose to replace the LLSE estimator by the Zero-Forcing (ZF) one. In order to better understand the perceived quality offered by these two estimators, a mathematical characterization as well as an objective and subjective studies are performed. Results show that the gains brought by the LLSE estimator, in terms of PSNR and Structural SIMiliraty (SSIM), are limited and quickly tend to null value as the CSNR increases. However, higher gains are obtained by the ZF estimator when considering the recent Video Multi-method Assessment Fusion (VMAF) metric proposed by Netflix, which evaluates the perceptual video quality. This result is confirmed by the subjective assessment.

关键词： SoftCast Linear Video coding Quality assessment Visual artifacts joint source-channel coding

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Deep FAVIB: Deep Learning-Based Forward-Aware Quantization via Information Bottleneck Method 59

Deep FAVIB: Deep Learning-Based Forward-Aware Quantization v...

引用

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

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

ISBN: (纸本)9781728190549

We focus on a (generic) joint source-channel coding problem, appearing in a broad variety of real-world application. Explicitly, a noisy observation from a user/source signal should be compressed, ahead of getting forwarded over an error-prone and rate-limited channel to a remote processing unit. The design problem shall be formulated in a fashion that the impacts of the forward link are taken into account. Aligned with the Information Bottleneck (IB) method, we consider the Mutual Information (MI) as the fidelity criterion, and work out a data-driven approach to tackle the underlying design problem based upon a finite sample set. For that, we derive a tractable variational lower-bound of the objective functional, and present a general learning architecture which can be used to optimize the given lower-bound by standard training of the encoder and decoder Deep Neural Networks. This approach that is, principally, based upon the (generative) latent variable models, extends the concepts of Variational AutoEncoder (VAE) and Deep Variational Information Bottleneck (Deep VIB) for (remote) source coding to the context of joint source-channel coding. We validate the effectiveness of our approach by several numerical simulations over typical transmission scenarios.

关键词： Information bottleneck variational autoencoder deep learning quantization joint source-channel coding 6G

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AirNet: Neural Network Transmission over the Air

AirNet: Neural Network Transmission over the Air

引用

IEEE International Symposium on Information Theory (ISIT)

作者： Jankowski, Mikolaj Gunduz, Deniz Mikolajczyk, Krystian Imperial Coll London Dept Elect & Elect Engn London England

ISBN: (纸本)9781665421607;9781665421591

State-of-the-art performance for many emerging edge applications is achieved by deep neural networks (DNNs). Often, the employed DNNs are location- and time-dependent, and the parameters of a specific DNN must be delivered from an edge server to the edge device rapidly and efficiently to carry out time-sensitive inference tasks. This can be considered as a joint source-channel coding (JSCC) problem, in which the goal is not to recover the DNN coefficients with the minimal distortion, but in a manner that provides the highest accuracy in the downstream task. For this purpose we introduce AirNet, a novel training and analog transmission method to deliver DNNs over the air. We first train the DNN with noise injection to counter the wireless channel noise. We also employ pruning to identify the most significant DNN parameters that can be delivered within the available channel bandwidth, knowledge distillation, and non-linear bandwidth expansion to provide better error protection for the most important network parameters. We show that AirNet achieves significantly higher test accuracy compared to the separation-based alternative, and exhibits graceful degradation with channel quality.

关键词： Neural network compression joint source-channel coding network pruning distributed inference

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A Measure for the Missed Error Detection Probability for Optimizing the Forbidden Symbol Configuration in joint source-channel Arithmetic Codes

A Measure for the Missed Error Detection Probability for Opt...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Kourkchi, Hossein Lynch, William E. Ahmad, M. Omair Concordia Univ Dept Elect & Comp Engn 1455 Maisonneuve Blvd W Montreal PQ H3G 1M8 Canada

ISBN: (纸本)9781479953417

In joint source-channel arithmetic coding, a forbidden symbol (FS) is added to the symbol set to make it more robust against transmission errors. By splitting the interval occupied by the FS into subintervals, various configurations are possible. In this paper, the delay probability function (DPF), the probability of the number of bits required to detect an error, is calculated for various FS configurations. A figure of merit is also proposed for optimizing the FS configuration. It determines the probability of missed error detection (PMD). Simulations are carried out by employing a breadth-first suboptimal sequential MAP. The simulation results show the effectiveness of the proposed figure of merit, and support the FS configuration in which the FS interval lies entirely between the other information carrying symbols to be the best.

关键词： Arithmetic coding maximum a posteriori (MAP) joint source-channel coding missed error detection

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A Novel Layered Error Resilient Method for SPIHT-Coded Images over Packet Networks

A Novel Layered Error Resilient Method for SPIHT-Coded Image...

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International Conference on Industry, Information System and Material Engineering

作者： Sun, WenZhu Wang, HongYu Wang, Jie Dalian Univ Technol Fac Elect Informat & Elect Engn Dalian 116023 Peoples R China

ISBN: (纸本)9783037850275

This paper presents a layered error resilient scheme for Set Partitioning in Hierarchical Trees (SPIHT) coding which incorporates the Multiple Description coding (MDC) into the data partition. The major feature of this scheme is that the MDC is adopted in the process of packetizing the spatial orientation trees, so as to protect the important information bits according to different importance and channel state. The proposed scheme can allocate redundancy accurately and flexibly, by differentiating importance of bits through different bit planes. Experimental results show that the proposed method achieves good performance over packet erasure channels.

关键词： Error-resilience multiple description coding bit plane coding set partitioning in hierarchical trees (SPIHT) joint source-channel coding

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COOPERATIVE LEARNING VIA FEDERATED DISTILLATION OVER FADING channelS

COOPERATIVE LEARNING VIA FEDERATED DISTILLATION OVER FADING ...

引用

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

作者： Ahn, Jin-Hyun Simeone, Osvaldo Kang, Joonhyuk Korea Adv Inst Sci & Technol Daejeon South Korea Kings Coll London London England

ISBN: (纸本)9781509066315

Cooperative training methods for distributed machine learning are typically based on the exchange of local gradients or local model parameters. The latter approach is known as Federated Learning (FL). An alternative solution with reduced communication overhead, referred to as Federated Distillation (FD), was recently proposed that exchanges only averaged model outputs. While prior work studied implementations of FL over wireless fading channels, here we propose wireless protocols for FD and for an enhanced version thereof that leverages an offline communication phase to communicate "mixed-up" covariate vectors. The proposed implementations consist of different combinations of digital schemes based on separate source-channel coding and of over-the-air computing strategies based on analog joint source-channel coding. It is shown that the enhanced version FD has the potential to significantly outperform FL in the presence of limited spectral resources.

关键词： Distributed training machine learning federated learning joint source-channel coding

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

On Asymptotic Analysis of Energy-Distortion Tradeoff for Low...

引用

IEEE International Symposium on Information Theory (ISIT)

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

ISBN: (纸本)9781538647813

Asymptotic energy-distortion performance of zero- and low-delay communication scenarios under additive white Gaussian noise (AWGN) is investigated. Using high-resolution analysis for quantizer design 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 increased considerably with respect to its naive value, i.e., that achieved by optimizing purely the source coding performance instead of the end-to-end distortion.

关键词： Energy-distortion dispersion energy-distortion tradeoff high-resolution quantization theory joint source-channel coding low-delay vector quantization zero-delay

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On the Analysis of Energy-Distortion Tradeoff for Zero-Delay Transmission over Gaussian Broadcast channels

On the Analysis of Energy-Distortion Tradeoff for Zero-Delay...

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IEEE International Symposium on Information Theory (ISIT)

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

ISBN: (纸本)9781538692912

Asymptotic energy-distortion performance of zero-delay communication under Gaussian broadcasting is investigated. The analysis can be motivated by the scenario where the same internet of things (IoT) device is transmitting its measurements to multiple control units that are experiencing varying noise levels. Using high-resolution analysis for quantizer design 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 value for the zero-delay regime.

关键词： Broadcast channels energy-distortion dispersion energy-distortion tradeoff high-resolution quantization theory joint source-channel coding succesive refinement zero-delay

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Distributed scalar quantizers for noisy channels

Distributed scalar quantizers for noisy channels

引用

32nd IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Karlsson, Johannes Wernersson, Niklas Skoglund, Mikael Royal Inst Technol Sch Elect Engn SE-10044 Stockholm Sweden

ISBN: (纸本)1424407281

Sensor nodes in wireless sensor networks should preferable be both cheap and energy efficient. To cope with these requirements an algorithm for designing distributed scalar quantizers optimized for noisy channels is proposed and evaluated. Applying the algorithm results in locally optimal systems. It is demonstrated that the correlation between the sources can be used to reduce the quantization distortion when the channel is close to error-free. If, on the other hand, there are a lot of disturbances on the channel the correlation can be used to introduce protection against channel errors.

关键词： multisensor systems distributed estimation quantization joint source-channel coding

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BANDWIDTH-REDUCTION ANALOG MAPPINGS FOR AWGN channelS WITH SIDE INFORMATION

BANDWIDTH-REDUCTION ANALOG MAPPINGS FOR AWGN CHANNELS WITH S...

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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 Inst Robot Technol Informt & las Comun Valencia 46980 Spain

ISBN: (纸本)9781467310680

Recently, the joint source-channel coding schemes based on analog mappings have gained prominence. Their simplicity and low delay compared to other coding strategies make them more suitable for real-time applications. In this work, we propose a novel joint source-channel coding scheme, based also on analog mappings, for a point-to-point communication channel with side information at the receiver (also known as Wyner-Ziv scenario).

关键词： joint source-channel coding Wyner-Ziv scenario analog mappings

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