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Learning Progressive distributed compression Strategies From Local Channel State Information

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2022年第3期16卷 573-584页

作者： Sohrabi, Foad Jiang, Tao Yu, Wei Univ Toronto Dept Elect & Comp Engn Toronto ON M5S 3G4 Canada

This paper proposes a deep learning framework to design distributed compression strategies in which distributed agents need to compress high-dimensional observations of a source, then send the compressed bits via bandwidth limited links to a fusion center for source reconstruction. Further, we require the compression strategy to be progressive so that it can adapt to the varying link bandwidths between the agents and the fusion center. Moreover, to ensure scalability, we investigate strategies that depend only on the local channel state information (CSI) at each agent. Toward this end, we use a data-driven approach in which the progressive linear combination and uniform quantization strategy at each agent are trained as a function of its local CSI. To deal with the challenges of modeling the quantization operations (which always produce zero gradients in the training of neural networks), we propose a novel approach of exploiting the statistics of the batch training data to set the dynamic ranges of the uniform quantizers. Numerically, we show that the proposed distributed estimation strategy designed with only local CSI can significantly reduce the signaling overhead and can achieve a lower mean-squared error distortion for source reconstruction than state-of-the-art designs that require global CSI at comparable overall communication cost.

关键词： Quantization (signal) Estimation Training Deep learning Bandwidth Wireless communication Signal processing algorithms Deep learning distributed compression distributed estimation progressive transmission quantization

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No Advantage of Non-Local Cooperation in distributed compression of Classical Sources

No Advantage of Non-Local Cooperation in Distributed Compres...

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2024 Information Theory Workshop

作者： Park, Hyun-Young Nam, Seung-Hyun Lee, Si-Hyeon Korea Adv Inst Sci & Technol KAIST Sch Elect Engn Daejeon South Korea

ISBN: (纸本)9798350348941;9798350348934

In this paper, we show that there is no advantage of using non-local cooperation between source encoders in improving the optimal compression rate (or rate region) for some canonical distributed compression tasks. The tasks are the lossless distributed compression, the lossless compression with a helper, and some special cases of the lossy distributed compression for 2-component discrete memoryless sources. These negative results for distributed source coding contrast with those for multi-user channel coding: quantum or general no-signaling cooperation between channel encoders improves the capacity region for some multiple access and interference channels.

关键词： distributed compression distributed source coding non-locality no-signaling quantum entanglement

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Robust distributed compression of Symmetrically Correlated Gaussian Sources

Robust Distributed Compression of Symmetrically Correlated G...

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作者： XUAN ZHANG Mcmaster University

学位级别：硕士

Consider a lossy compression system with ' distributed encoders and a centralized decoder. Each encoder compresses its observed source and forwards the compressed data to the decoder for joint reconstruction of the target signals under the mean squared error distortion constraint. It is assumed that the observed sources can be expressed as the sum of the target signals and the corruptive noises, which are gen- erated independently from two (possibly different) symmetric multivariate Gaussian distributions. Depending on the parameters of such Gaussian distributions, the rate- distortion limit of this lossy compression system is characterized either completely or for a subset of distortions (including, but not necessarily limited to, those sufficiently close to the minimum distortion achievable when the observed sources are directly available at the decoder). The results are further extended to the robust distributed compression setting, where the outputs of a subset of encoders may also be used to produce a non-trivial reconstruction of the corresponding target signals. In particu- lar, we obtain in the high-resolution regime a precise characterization of the minimum achievable reconstruction distortion based on the outputs of k + 1 or more encoders when every k out of all ' encoders are operated collectively in the same mode that is greedy in the sense of minimizing the distortion incurred by the reconstruction of the corresponding k target signals with respect to the average rate of these k encoders.

关键词： distributed compression Gaussian source Karush-Kuhn-Tucker condi-tions mean squared error rate-distortion

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Theoretical investigation of a novel distributed compression cycle for CO2 trans-critical system

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ENERGY AND BUILDINGS 2024年 304卷

作者： Wang, Lei Zhang, Yumei Ma, Guoyuan Beijing Univ Technol Dept Refrigerat & Cryogen Engn Beijing 100124 Peoples R China

Efficient cooling of the trans-critical CO2 vapor compression cycle to improve system performance is a crucial research topic. This paper proposes an innovative approach called distribution compression (DC) to achieve the same effect as subcooling in a trans-critical CO2 thermodynamic cycle. In the DC system, the trans-critical CO2 at the gas cooler outlet is no longer further cooled but subjected to a secondary pressure boost and releases heat in ordinary heat sink conditions as in the gas cooler. Thermodynamics calculated the change in performance of the DC system under different working conditions with different secondary boost ratios. The optimal secondary boost ratio related to evaporation and gas cooler outlet temperatures under optimal discharge pressure based on the baseline system was obtained. The results show that compared with the baseline system, the DC system can effectively improve the system performance, and the maximum refrigeration COP increase is between 8.2 % -10.76 %, and the maximum heating COP increase is between 5.37 % -6.34 %. The cooling or heating capacity increase can reach up to about 26 %. The ideal secondary boost ratio in a DC system is not highly demanding, and the increased input power for the second input power for the secondary boost will not exceed 20 % relative to the baseline system. Comparing the COP of the DC system over current systems that only use a single subcooling technology still shows advantages. The DC system provides a new idea to improve the performance of the transcritical CO2 vapor compression cycle.

关键词： distributed compression CO2 Trans-critical cycle Subcooling Refrigeration Heating

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High-efficiency distributed Image compression Algorithm Based on Soft Threshold Iteration for Wildlife Images with Wireless Image Sensor Networks

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SENSORS AND MATERIALS 2024年第6期36卷 2521-2538页

作者： Feng, Wenzhao Dong, Xiang Li, Jiancheng Yang, Ziqian Niu, Qingyu Shijiazhuang Tiedao Univ Hebei Prov Collaborat Innovat Ctr Transportat Powe Shijiazhuang 050043 Peoples R China Shijiazhuang Tiedao Univ Sch Elect & Elect Engn Shijiazhuang 050043 Peoples R China

Wireless image sensor networks (WISNs) are widely applied in wildlife protection as they present a better performance in remote, real-time monitoring. However, traditional WISNs suffer from the limitations of low processing capability, power consumption restrictions, and narrow transmission bandwidth, which leads to a shorter working lifetime of the monitoring system when transmitting the wildlife monitoring image with high resolution. We propose a high -efficiency distributed image compression coding method based on soft threshold iteration and quantitative perception for wildlife monitoring images to rationally assign the electricity resource. Specifically, we first utilize the histogram contrast algorithm to detect the saliency object region from the original samples and use it to generate the mask image of the wildlife region. After the mask image is obtained, the distributed image compression coding method is utilized to transmit the wildlife image, in which the saliency image region is directly transmitted as a cluster head to ensure the transmission efficiency of the wildlife region. Then the background region is assigned to the other four monitoring nodes at the same level for processing and transmission, extending the lifetime of the network. Furthermore, the soft threshold iteration algorithm is utilized to encode the image data;this is suitable for WISNs. The experimental results on our own wildlife dataset show improvements of 7.47 and 9.06% for the peak signal-tonoise ratio and 16.98 and 19.50% for the structural similarity index on the reconstructed image compared with those of the discrete cosine transform and embedded zerotree wavelets algorithms, respectively. Compared with the multihop and single -hop transmission methods, the power consumption is reduced by 29.96 and 40.84%, respectively. The results of this study indicate that the WISN technique can provide feasible solutions for the intelligent monitoring of forest biological resources.

关键词： distributed compression soft threshold iteration wildlife monitoring image saliency detection WISNs

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Theoretical analysis and digital photoelastic measurement of circular disks subjected to partially distributed compressions

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EXPERIMENTAL MECHANICS 2003年第2期43卷 216-224页

作者： Hung, KM Ma, CC Natl Taiwan Univ Dept Engn Mech Taipei 10617 Taiwan

The disk in diametral compression has been quoted most frequently on developing conventional/digital photoelasticity to illustrate new theories and experimental techniques for several decades. Theoretically, the compression as a concentrated force is more conducive to analysis, but it is impossible to achieve such loading condition experimentally. The distributed compression on a finite area at rim is relatively closer to actual testing and it is complicated to seek an analytical solution. In this paper, we extend the work of Hondros to derive the full-field stress distribution of disk subjected to diametral distributed compression in an explicit functional form. The principal stress difference and principal stress orientation related to isochromatic and isoclinic fringes, respectively, are also expressed in a simple closed form. The maximum shear stress for the whole disk and the validity of using isochromatic fringes to interpret the maximum shear stress are discussed in detail. The isoclinic fringes are compared with theory, and the fringe multiplication isochromatic is compared with simulated image. All of the comparisons are in good agreement with respect to full field.

关键词： disk distributed compression digital photoelasticity isochromatics isoclinics principal stress

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On Practical Design for Joint distributed Source and Network Coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2009年第4期55卷 1709-1720页

作者： Wu, Yunnan Stankovic, Vladimir Xiong, Zixiang Ming, Sun-Yuan Microsoft Res Olympia WA 98502 USA Univ Strathclyde Dept Elect & Elect Engn Glasgow G1 1XW Lanark Scotland Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA Princeton Univ Dept Elect Engn Princeton NJ 08544 USA

This paper considers the problem of communicating correlated information from multiple source nodes over a network of noiseless channels to multiple destination nodes, where each destination node wants to recover all sources. The problem involves a joint consideration of distributed compression and network information relaying. Although the optimal rate region has been theoretically characterized, it was not clear how to design practical communication schemes with low complexity. This work provides a partial solution to this problem by proposing a low-complexity scheme for the special case with two sources whose correlation is characterized by a binary symmetric channel. Our scheme is based on a careful combination of linear syndrome-based Slepian-Wolf coding and random linear mixing (network coding). It is in general suboptimal, however, its low complexity and robustness to network dynamics make it suitable for practical implementation.

关键词： Network coding distributed source coding distributed compression multicast low complexity

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Quantizer Design for Energy-Based Source Localization in Sensor Networks

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2011年第11期59卷 5577-5588页

作者： Kim, Yoon Hak Ortega, Antonio Samsung Elect Syst LSI Div Gyeonggi Do 446711 South Korea Univ So Calif Dept Elect Engn Signal & Image Proc Inst Los Angeles CA 90089 USA

We consider energy-based source localization applications, where distributed sensors quantize acoustic signal energy readings and transmit quantized data to a fusion node, which then produces an estimate of the source location. We propose an iterative quantizer design algorithm that allows us to take into account localization accuracy for quantizer design in the framework of the generalized Lloyd algorithm. Since source coding methodologies based on the Lloyd algorithm suffer from the presence of numerous poor local optima depending on initialization of quantizers, we introduce an efficient initialization, the equally distance-divided quantizer (EDQ), designed so that quantizer partitions correspond to a uniform partitioning in terms of distance. Our simulations demonstrate that improved performance over traditional quantizer designs can be achieved by using our proposed application specific strategy.

关键词： distributed compression distributed source coding (DSC) generalized Lloyd algorithm quantizer design sensor networks source localization

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Data Extraction from Wireless Sensor Networks Using distributed Fountain Codes

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IEEE TRANSACTIONS ON COMMUNICATIONS 2009年第9期57卷 2607-2618页

作者： Oka, Anand Lampe, Lutz Univ British Columbia Dept Elect & Comp Engn Vancouver BC V5Z 1M9 Canada

A Wireless Sensor Network (WSN) observes a natural field and aims to recreate it with sufficient fidelity at a, perhaps distant, Fusion Center (FC) using a wireless communication channel of arbitrary capacity. We propose a universal and power efficient method for such data extraction, based on Digital Fountain Codes (DFCs) and joint-source channel decoding. Our method implements a distributed 'rate-less' DFC which automatically tunes the number of transmissions to the channel capacity. Furthermore, instead of directly compressing the WSN data, we achieve rate reduction by treating the spatiotemporal dependencies in the field as an outer code, and jointly decoding this concatenation at the FC using a multi-stage iterative decoder. We demonstrate that a power efficiency close to the capacity-rate-distortion limit is achieved at moderate distortion levels, irrespective of the channel capacity or field dependencies. As compared to the traditional approach of source-channel separation, the proposed data extraction scheme is particularly attractive for WSN applications due its computationally simple encoding procedure, low latency and the ability to seamlessly trade-off fidelity of reconstruction for power consumption.

关键词： Wireless sensor networks distributed compression joint source-channel decoding fountain codes

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Joint Reconstruction of Multiview Compressed Images

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2013年第5期22卷 1969-1981页

作者： Thirumalai, Vijayaraghavan Frossard, Pascal Ecole Polytech Fed Lausanne Signal Proc Lab LTS4 Inst Elect Engn CH-1015 Lausanne Switzerland

distributed representation of correlated multiview images is an important problem that arises in vision sensor networks. This paper concentrates on the joint reconstruction problem where the distributively compressed images are decoded together in order to take benefit from the image correlation. We consider a scenario where the images captured at different viewpoints are encoded independently using common coding solutions (e. g., JPEG) with a balanced rate distribution among different cameras. A central decoder first estimates the inter-view image correlation from the independently compressed data. The joint reconstruction is then cast as a constrained convex optimization problem that reconstructs total-variation (TV) smooth images, which comply with the estimated correlation model. At the same time, we add constraints that force the reconstructed images to be as close as possible to their compressed versions. We show through experiments that the proposed joint reconstruction scheme outperforms independent reconstruction in terms of image quality, for a given target bit rate. In addition, the decoding performance of our algorithm compares advantageously to state-of-the-art distributed coding schemes based on motion learning and on the DISCOVER algorithm.

关键词： Depth estimation distributed compression joint reconstruction multiview images optimization proximal splitting

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