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检索条件"主题词=distributed compression"

共 54 条记录，以下是41-50 订阅

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CONTENT ADAPTIVE GOP SIZE CONTROL WITH FEEDBACK CHANNEL SUPPRESSION IN distributed VIDEO CODING

CONTENT ADAPTIVE GOP SIZE CONTROL WITH FEEDBACK CHANNEL SUPP...

引用

16th IEEE International Conference on Image Processing

作者： Yaacoub, Charles Farah, Joumana Pesquet-Popescu, Beatrice Holy Spirit Univ Kaslik Fac Sci & Comp Engn Jounieh Lebanon Telecom Paris Tech Signal & Image Processing Paris France

ISBN: (纸本)9781424456536

This paper presents a novel algorithm for content adaptive GOP size control in distributed video coding. The GOP size is dynamically varied along the sequence, depending on motion activity. Automatic mode selection allows the system to switch between H.264 intra-coding and Wyner-Ziv coding modes to optimize the overall performance. Furthermore, the encoder determines a suitable compression ratio for the Wyner-Ziv frames without the need for a feedback channel. Simulation results show significant improvement in the average system performance, compared to fixed GOP Wyner-Ziv and H.264 intra-coding.

关键词： Video distributed compression GOP size control return channel Wyner-Ziv

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PERFORMANCE OF THE distributed KLT AND ITS APPROXIMATE IMPLEMENTATION

PERFORMANCE OF THE DISTRIBUTED KLT AND ITS APPROXIMATE IMPLE...

引用

20th European Signal Processing Conference (EUSIPCO)

作者： Lara, Mauricio Mulgrew, Bernard IPN CINVESTAV Secc Comunicac Av IPN 2508 Mexico City 07360 DF Mexico Univ Edinburgh Inst Digital Commun Edinburgh EH9 3JL Midlothian Scotland

ISBN: (纸本)9781467310680

The Karhunen-Loeve Transform (KLT) is an important processing tool in data compression. Recently, a distributed version of the KLT was introduced together with an iterative algorithm for its implementation. Then, a recursive greedy algorithm for its approximate implementation was presented. Performance evaluations of both algorithms in the literature have been based on a few toy examples, which is not enough to show the intricacies of the distributed KLT. In this paper, a multi-terminal Markov-chain model is presented and used to evaluate the KLT algorithms using a large number of randomly generated covariance matrices. One of the findings is that the recursive greedy algorithm does not perform as well as predicted, and thus a variation of this algorithm is proposed which outperforms the original one. Finally, a promising application for both approximate algorithms is considered when the optimal distribution of the transmitted vectors among terminals is to be obtained.

关键词： distributed compression distributed transforms distributed KLT multi-terminal model

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Correlated Sources with Actions

Correlated Sources with Actions

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51st IEEE Annual Allerton Conference on Communication, Control, and Computing

作者： Sabag, Oron Permuter, Haim H. Cohen, Asaf Ben Gurion Univ Negev IL-84105 Beer Sheva Israel

ISBN: (纸本)9781479934096

In this paper, we consider the problem of distributed compression of correlated sources with action-dependent joint distribution. This setup is an extension of the SlepianWolf model, but where actions taken by the encoder or the decoder and affect the generation of one of the sources. In both cases, we characterize the set of achievable rates completely, and show how the actions in the system affect the rate region in a nontrivial manner. We further study a network coding problem in a general network setup with two sources and one destination, where actions are taken at the encoder. In this case, we derive generalized cut-set bounds, and characterize the set of achievable rates using single letter expressions.

关键词： Actions distributed compression random binning network coding random linear coding

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distributed Uplink Reception for D2D Underlaid C-RAN Systems With Fronthaul Constraints 88

Distributed Uplink Reception for D2D Underlaid C-RAN Systems...

引用

88th IEEE Vehicular Technology Conference (VTC-Fall)

作者： Kim, Junbeom Yu, Daesung Choi, In-Kyeong Hong, Seung-Eun Park, Seok-Hwan Chonbuk Natl Univ Div Elect Engn Jeonju South Korea Elect & Telecommun Res Inst Daejeon South Korea

ISBN: (纸本)9781538663585

This work studies distributed uplink reception for a device-to-device (D2D) underlaid cloud radio access network (C-RAN) system, in which cellular user equipments (UEs) communicate with a baseband processing unit (BBU) through a set of distributed remote radio heads (RRHs) that are connected to the BBU via finite-capacity fronthaul links. The uplink of C-RAN system is interfered by a number of D2D communication links that operate in the same frequency band. Most of prior works on C-RAN uplink systems prescribe that the noise signals of different RRHs do not have statistical correlation. However, in the D2D underlaid C-RAN uplink systems, the effective noise signals that contain the D2D interference signals may have inter-RRH cross correlation. This work proposes an improved distributed reception scheme which leverages the noise correlation information. To tackle non-convex sum-rate maximization problem, a successive convex approximation (SCA) based iterative algorithm is derived that guarantees monotonically non-decreasing sum-rates. Some numerical results are presented that validate the advantages of the proposed scheme.

关键词： C-RAN D2D fronthaul quantization distributed compression beamforming

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Joint Signal and Channel State Information compression for Uplink Network MIMO Systems

Joint Signal and Channel State Information Compression for U...

引用

IEEE Global Conference on Signal and Information Processing (GlobalSIP)

作者： Kang, Jin-Kyu Simeone, Osvaldo Kang, Joonhyuk Shamai (Shitz), Shlomo Korea Adv Inst Sci & Technol Dept Elect Engn Taejon 305701 South Korea NJIT CWCSPR Newark NJ USA Technion Israel Inst Technol Dept Elect Engn IL-32000 Haifa Israel

ISBN: (纸本)9781479902484

In the uplink of network MIMO systems, in order to cope with backhaul capacity limitations, base stations (BSs) must compress the received baseband data signal and the channel state information (CSI) for communication to the central unit (CU). Assuming ergodic fading, an Estimate-Compress-Forward (ECF) approach is investigated, whereby the BSs perform CSI estimation and forward a compressed version of the CSI to the CU. This approach contrasts with the previously studied Compress-Forward-Estimate (CFE) strategy, whereby CSI estimation is performed at the CU, and is motivated by the information-theoretic optimality of separate estimation and compression. Various ECF schemes are proposed that perform either separate or joint compression of estimated CSI and received baseband signal. Via numerical results, it is shown that a proper design of ECF strategies leads to substantial performance gains compared to the CFE approach.

关键词： Uplink network MIMO limited backhaul imperfect CSI compress and forward distributed compression

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distributed ADAPTIVE EIGENVECTOR ESTIMATION OF THE SENSOR SIGNAL COVARIANCE MATRIX IN A FULLY CONNECTED SENSOR NETWORK

DISTRIBUTED ADAPTIVE EIGENVECTOR ESTIMATION OF THE SENSOR SI...

引用

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

作者： Bertrand, Alexander Moonen, Marc Katholieke Univ Leuven Dept ESAT SCD Kasteelpk Arenberg B-3001 Leuven Belgium Katholieke Univ Leuven iMinds Future Hlth Dept B-3001 Leuven Belgium

ISBN: (纸本)9781479903566

In this paper, we describe a distributed adaptive (time-recursive) algorithm to estimate and track the eigenvectors corresponding to the Q largest or smallest eigenvalues of the global sensor signal covariance matrix in a wireless sensor network (WSN). We only address the case of fully connected (broadcast) networks, in which the nodes broadcast compressed Q-dimensional sensor observations. It can be shown that the algorithm converges to the desired eigenvectors without explicitely constructing the global covariance matrix that actually defines them, i.e., without the need to centralize all the raw sensor observations. The algorithm allows each node to estimate (a) the node-specific entries of the global covariance matrix eigenvectors, and (b) Q-dimensional observations of the full set of sensor observations projected onto the Q estimated eigenvectors. The theoretical results are validated by means of numerical simulations.

关键词： Wireless sensor networks distributed estimation distributed compression distributed eigenvector estimation

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distributed ADAPTIVE ESTIMATION OF CORRELATED NODE-SPECIFIC SIGNALS IN A FULLY CONNECTED SENSOR NETWORK

DISTRIBUTED ADAPTIVE ESTIMATION OF CORRELATED NODE-SPECIFIC ...

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Bertrand, Alexander Moonen, Marc Katholieke Univ Leuven Dept ESAT B-3001 Louvain Belgium

ISBN: (纸本)9781424423538

We introduce a distributed adaptive estimation algorithm operating in an ideal fully connected sensor network. The algorithm estimates node-specific signals at each node based on reduced-dimensionality sensor measurements of other nodes in the network. If the node-specific signals to be estimated are linearly dependent on a common latent process with a low dimension compared to the dimension of the sensor measurements, the algorithm can significantly reduce the required communication bandwidth and still provide the optimal linear estimator at each node as if all sensor measurements were available in every node. Because of its adaptive nature and fast convergence properties, the algorithm is suited for real-time applications in dynamic environments, such as speech enhancement in acoustic sensor networks.

关键词： distributed estimation wireless sensor networks (WSNs) adaptive estimation distributed compression

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Problems on Large Sparse Graphs

Problems on Large Sparse Graphs

引用

作者： Delgosha, Payam University of California Berkeley

学位级别：Ph.D., Doctor of Philosophy

In this thesis, we study two category of problems involving large sparse graphs, namely the problem of compression for graphical data, and load balancing in networks. We achieve this by employing the framework of local weak convergence, or so called the objective method. This framework provides a viewpoint which enables one to make sense of a notion of stationary stochastic processes for sparse *** employing the local weak convergence framework, we introduce a notion of entropy for probability distributions on rooted graphs. This is a generalization of the notion of entropy introduced by Bordenave and Caputo to graphs which carry marks on their vertices and edges. Such marks can represent information on real-world data. This notion of entropy can be considered as a natural counterpart for the Shannon entropy rate in the world of sparse graphical data. We illustrate this by introducing a universal compression scheme for sparse marked graphs. Furthermore, we study distributed compression of graphical data. In particular, we introduce a version of the Slepian–Wolf theorem for sparse marked *** addition to studying the problem of compression, we study the problem of load balancing in networks. We do this by modeling the problem as a hypergraph where each hyperedge represents a task carrying one unit of load, and each vertex represents a server. An allocation is a way of distributing this load. we study balanced allocations, which are roughly speaking those allocations in which no demand desires to change its allocation. Employing an extension of the local weak convergence theory to hypergraphs, we study certain asymptotic behaviors of balanced allocations, such as the asymptotic empirical load distribution at a typical server, as well as the asymptotic of the maximum *** studied in this thesis should be considered as examples showing the wide-range applicability of the local weak convergence theory and the above mentioned notion of entropy. In fact

关键词： Data compression distributed compression Load balancing Local weak convergence Sparse graphs Universal compression

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New results of efficient Slepian-Wolf compression using turbo codes

New results of efficient Slepian-Wolf compression using turb...

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6th IASTED International Conference on Signal and Image Processing

作者： Li, J Lehigh Univ Dept Elect & Comp Engn Bethlehem PA 18015 USA

ISBN: (纸本)0889864349

We introduce a new innovation for exploiting the algebraic binning scheme with turbo codes in distributed source coding (DSC). A simple and optimal turbo-binning scheme based on syndrome former (SF) and inverse syndrome former (ISF) was proposed in [1], but the SF/ISF construction therein works for non-punctured codes only. Since punctured turbo codes are an important class of codes, this work extends it to the punctured case. The key is to represent the punctured code in an equivalent non-punctured form and to construct the SF and ISF accordingly. We show that with punctured codes, the turbo-binning scheme is still simple, efficient and optimal. Further, the extension not only makes a large class of powerful turbo codes available to DSC, but also opens the possibility to explore rate adaptivity in turbo codes.

关键词： distributed source coding distributed compression code binning turbo codes punctured codes

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distributed signal estimation in a wireless sensor network with partially-overlapping node-specific interests or source observability 40

Distributed signal estimation in a wireless sensor network w...

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40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015

作者： Plata-Chaves, Jorge Bertrand, Alexander Moonen, Marc KU Leuven Dept. Electrical Engineering ESAT Stadius Center for Dynamical Systems Signal Processing and Data Analytics Kasteelpark Arenberg 10 Leuven Belgium

ISBN: (纸本)9781467369978

We study a distributed node-specific signal estimation problem where the node-specific desired signals and/or the sensor observations can have partially-overlapping latent signal subspaces. First, we provide the minimum number of linear combinations of observed sensor signals that each node can broadcast to still let all other nodes achieve the network-wide Linear Minimum Mean-Square Error (LMMSE) estimate of their node-specific desired signals. Later, for a fully-connected wireless sensor network, we derive a distributed algorithm that, under some settings, allows each node to achieve the LMMSE estimate of its node-specific desired signals by broadcasting the smallest number of signals. Unlike the existing algorithms, the proposed algorithm deals with the problem of partially-overlapping node-specific interests and incomplete observability of all latent sources at the nodes. Finally, the effectiveness of the proposed technique is shown through numerical simulations. © 2015 IEEE.

关键词： distributed compression distributed signal estimation wireless sensor networks

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