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IEEE Vehicular Technology Conference

作者： Mojtaba Vaezi Fabrice Labeau Department of Electrical and Computer Engineering McGill University

ISBN: (纸本)9781467318808

We show how real-number codes can be used to compress correlated sources, and establish a new framework for distributed lossy source coding, in which we quantize compressed sources instead of compressing quantized sources. This change in the order of binning and quantization blocks makes it possible to model correlation between continuous-valued sources more realistically and correct quantization error when the sources are completely correlated. The encoding and decoding procedures are described in detail, for discrete Fourier transform (DFT) codes. Reconstructed signal, in the mean-squared error sense, is seen to be better than or close to quantization error level in the conventional approach.

关键词： distributed source coding Real-number codes BCH-DFT codes Channel coding Wyner-Ziv coding lossy source coding Quantization Real number discrete Fourier transform change orders Codes COMPRESSED Distribute

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DESIGN OF BINARY LDPC CODES FOR SLEPIAN-WOLF coding OF CORRELATED INFORMATION sourceS 5

DESIGN OF BINARY LDPC CODES FOR SLEPIAN-WOLF CODING OF CORRE...

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5th IEEE Global Conference on Signal and Information Processing (GlobalSIP)

作者： Eleruja, Saeed Abdu-Aguye, Umar-Faruk Ambroze, Marcel Tomlinson, Martin Zaki, Mohammed Plymouth Univ Sch Comp Elect & Math Plymouth Devon England

ISBN: (纸本)9781509059904

In this paper, we propose a scheme for distributed source coding, using low-density parity-check (LDPC) codes to compress close to the Slepian-Wolf limit for correlated binary sources. First, we develop a conventional Belief Propagation (BP) algorithm LDPC decoder which takes the syndrome information into account. Subsequently, modelling the correlation between the sources as a binary symmetric channel (BSC), we replace the received probabilities in the conventional channel with the cross over probability. The performance achieved is seen to be better than previously published schemes for similar block length and code rate.

关键词： distributed source coding syndrome approach LDPC codes Slepian-Wolf theorem

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Generalized distributed compressive sensing with security challenges for linearly correlated information sources

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2018年第3期30卷

作者： Park, Jeonghun Hwang, Seunggye Yang, Janghoon Bae, Kitae Ko, Hoon Kim, Dong Ku Univ Texas Austin Dept Elect & Comp Engn Austin TX 78712 USA LG Elect Anyang South Korea Seoul Media Inst Technol Dept New Media Seoul South Korea Sungkyunkwan Univ Coll Informat & Commun Engn Suwon South Korea Yonsei Univ Sch Elect & Elect Engn Seoul South Korea

distributed compressive sensing (DCS) usually improves the signal recovery performance of multi-signal ensembles by exploiting both intra- and inter-signal correlation and sparsity structure. However, the existing DCS had proposed for a very limited ensemble of signals that has only single common information. This paper proposes a generalized DCS (GDCS) framework which can improve sparse signal detection performance given arbitrary types of common information, which are classified into full common information and partial common information after overcoming against existing limitation. Specifically, the theoretical bound on the required number of measurements under the GDCS is obtained. We also develop a practical algorithm to obtain benefits using the GDCS. At the end of this paper, it simply summarizes the potential security issues when it gets all sensing information in a sensor network. Finally, numerical results verify that the proposed algorithm reduces the required number of measurements for correlated sparse signal detection compared to the DCS algorithm. This research lays down the basis for efficient distributed signal detection so that it can improve the detection performance or it can detect the signal reliably when the number of signal observations is limited.

关键词： compressive sensing distributed source coding security sensor networks sparsity

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Systematic Polar Codes for Joint source-Channel coding in Wireless Sensor Networks and the Internet of Things

Systematic Polar Codes for Joint Source-Channel Coding in Wi...

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14th International Conference on Mobile Systems and Pervasive Computing (MobiSPC) / 12th International Conference on Future Networks and Communications (FNC)

作者： Yaacoub, Charles Sarkis, Malak Holy Spirit Univ Kalsik USEK Dept Telecommun Fac Engn POB 446 Jounieh Lebanon NH USA

The Internet of Things (IoT) is becoming an increasingly growing topic of interest in the research community. Its requirements meet those of the next generation 5G mobile communication system which is expected to be an enabling technology for IoT, where networks of large numbers of sensors require massive connectivity demands. As polar codes have strongly entered into action within the standardization of 5G, this paper proposes and investigates the use of systematic polar codes for joint-source channel coding of correlated sources thus allowing, on one hand, the compression of the volume of data to be transmitted over the network, and on the other hand, the protection of this data from channel impairments. Results show that systematic polar codes can achieve a distributed compression with rates close to the theoretical bound, with better error rates obtained for larger blocks. However, stronger compression and shorter block lengths allow for a better robustness against transmission errors. (C) 2017 The Authors. Published by Elsevier B.V.

关键词： channel coding compression distributed source coding entropy internet of things systematic polar codes wireless sensor networks

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SLEPIAN-WOLF VIDEO coding WITH RESOLUTION-PROGRESSIVE TRANSMISSION 25

SLEPIAN-WOLF VIDEO CODING WITH RESOLUTION-PROGRESSIVE TRANSM...

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International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Nakachi, Takayuki Ishihara, Shinya Nippon Tel & Telegraph Corp NTT Network Innovat Labs 1-1 Hikarino Oka Yokosuka Kanagawa 2390847 Japan

ISBN: (纸本)9781538621592

In this paper, we propose a new Slepian-Wolf (SW) video coding that supports resolution-progressive transmission. It can realize low-delay low-resolution real time streaming as well as high lossless coding efficiency. Intra-frame video coding is performed as the base layer coder for down-sampled input video and a SW coder is used as the enhancement layer coder for lossless archiving. In order to improve SW loss less coding efficiency, we introduce inter-layer prediction between the base layer and the enhancement layer. It uses inter layer prediction to increase the accuracy of Motion Estimation (ME). Simulations show that the proposed scheme gives higher coding performance better than the JPEG2000 lossless mode.

关键词： distributed source coding Slepian-Wolf Theorem Lossless Video coding Video Transmission Layered Video coding Media Collaboration

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Temporal-Spatial Symmetric distributed Multi-View Video coding Scheme

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 2017年第8期31卷 1755011-1755011页

作者： Zhang, Guoyun Xiang, Canqun Ou, Xianfeng Yue, Hong Guo, Longyuan Wu, Jianhui Tu, Bing He, Wei Hunan Inst Sci & Technol Coll Informat & Commun Engn Yueyang 414006 Peoples R China Hunan Inst Sci & Technol Key Lab Optimizat & Control Complex Syst Yueyang 414006 Peoples R China SIPO Patent Off Patent Examinat Cooperat Ctr Chengdu 610000 Sichuan Peoples R China

To improve the rate stability and make a balance for different viewpoints in distributed multi-view video coding (DMVC) system, a novel symmetric DMVC (SDMVC) scheme is proposed in this paper. In the proposed scheme, every frame from all views adopts the same encoding mode and stable output rates are achieved, which are significant to improve the transmission efficiency in the channel. Both temporal and spatial correlations are exploited, in addition, a novel side information (SI) generation algorithm aiming at better exploring the correlations of proposed scheme has been proposed to obtain better performance. The simulation results show that the proposed SDMVC scheme gets a much more stable rate than the asymmetric scheme, only with neglectable bit-rate increasing. Meanwhile, the proposed SI generation algorithm significantly improves the coding performance.

关键词： distributed source coding symmetric distributed multi-view video coding side information generation stable bit rate

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Systematic Polar Codes for Joint source-Channel coding in Wireless Sensor Networks and the Internet of Things

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Procedia Computer Science 2017年 110卷 266-273页

作者： Charles Yaacoub Malak Sarkis Department of Telecommunications Faculty of Engineering Holy Spirit University of Kalsik (USEK) P.O.Box 446 Jounieh Lebanon

关键词： channel coding compression distributed source coding entropy internet of things systematic polar codes wireless sensor networks

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distributed lossy compression for hyperspectral images based on multilevel coset codes

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INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING 2017年第2期15卷 1750012-1750012页

作者： Xu, Ke Liu, Bin Nian, Yongjian He, Mi Wan, Jianwei Natl Univ Def Technol Coll Elect Sci & Engn Changsha 410073 Hunan Peoples R China Jinan Mil Area Command Gen Hosp Dept Med Informat Jinan 250031 Peoples R China Third Mil Med Univ Sch Biomed Engn Chongqing 400038 Peoples R China

This paper focuses on the problem of lossy compression for hyperspectral images and presents an efficient compression algorithm based on distributed source coding. The proposed algorithm employs a block-based quantizer followed by distributed lossless coding, which is implemented through the use of multilevel coset codes. First, a bitrate allocation algorithm is proposed to assign the rational bitrate for each block. Subsequently, the multilinear regression model is employed to construct the side information of each block, and the optimal quantization step size of each block is obtained under the assigned bitrate while minimizing the distortion. Finally, the quantized version of each block is encoded by distributed lossless compression. Experimental results show that the compression performance of the proposed algorithm is competitive with that of state-of-the-art transformbased compression algorithms. Moreover, the proposed algorithm provides both low encoder complexity and error resilience, making it suitable for onboard compression.

关键词： Hyperspectral images lossy compression distributed source coding bitrate allocation error resilience

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distributed source coding AND DISPERSIVE INFORMATION ROUTING : AN INTEGRATED APPROACH WITH NETWORKING AND DATABASE APPLICATIONS

DISTRIBUTED SOURCE CODING AND DISPERSIVE INFORMATION ROUTING...

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18th European Signal Processing Conference (EUSIPCO)

作者： Viswanatha, Kumar Akyol, Emrah Ramaswamy, Sharadh Rose, Kenneth Univ Calif Santa Barbara Dept Elect & Comp Engn Santa Barbara CA 93106 USA

This paper considers the design of optimal joint compression-routing schemes for networks with correlated sources and multiple sinks. Such a setting is typically encountered in sensor networks. It is sometimes tempting to assume that an optimal distributed compression scheme followed by standard routing (as designed for independent sources) would be nearly optimal. We instead propose a joint design approach that integrates distributed source coding with a mechanism called dispersive information routing. Unlike network coding, dispersive information routing can be realized using conventional routers without recourse to recoding at intermediate nodes. We also point out the direct connections between dispersive information routing and a related problem in sensor network databases, namely, fusion coding for selective retrieval. We propose an efficient practical design strategy, variants of which are adopted for each of the two problems. Simulation results provide evidence for substantial gains over conventional schemes.

关键词： Compression distributed source coding routing sensor networks database retrieval

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distributed source coding in Large Wireless Sensor Networks

Distributed Source Coding in Large Wireless Sensor Networks

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44th Asilomar Conference on Signals, Systems and Computers

作者： Barcelo-Llado, J. E. Morell, Antoni Seco-Granados, Gonzalo Univ Autonoma Barcelona Dpt Telecom & Syst Engn E-08193 Barcelona Spain

ISBN: (纸本)9781424497218

We study the performance of distributed source coding in large wireless sensor networks obtained with enhanced correlation estimators. distributed source coding is especially useful when data correlation exists since it tries to remove the redundancy in the information;and dense sensor networks are rich in correlations. Existing results from information theory show that this compression can be executed in a distributed fashion and without any performance loss in comparison with the centralized approach. However, there is still performance gap between the theoretical bounds and the results achieved with practical implementations. In order to mitigate this, we propose the use of enhanced correlation estimators. Simulation results show a performance improvement in the energy consumption by reducing the number of transmitted bits compared to classical methods.

关键词： C-2 E-6 distributed source coding Wireless sensor networks source coding energy consumption data association performance boost Sensor networks Information Theory Estimators

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