检索结果-内蒙古大学图书馆

The CEO Problem With Inter-Block Memory

IEEE TRANSACTIONS ON INFORMATION THEORY 2021年第12期67卷 7752-7768页

作者： Kostina, Victoria Hassibi, Babak CALTECH Dept Elect Engn Pasadena CA 91125 USA

An n-dimensional source with memory is observed by K isolated encoders via parallel channels, who compress their observations to transmit to the decoder via noiseless rate-constrained links while leveraging their memory of the past. At each time instant, the decoder receives K new code-words from the observers, combines them with the past received code-words, and produces a minimum-distortion estimate of the latest block of n source symbols. This scenario extends the classical one-shot CEO problem to multiple rounds of communication with communicators maintaining the memory of the past. We extend the Berger-Tung inner and outer bounds to the scenario with inter-block memory, showing that the minimum asymptotically (as n -> infinity) achievable sum rate required to achieve a target distortion is bounded by minimal directed mutual information problems. For the Gauss-Markov source observed via K parallel AWGN channels, we show that the inner bound is tight and solve the corresponding minimal directed mutual information problem, thereby establishing the minimum asymptotically achievable sum rate. Finally, we explicitly bound the rate loss due to a lack of communication among the observers;that bound is attained with equality in the case of identical observation channels. The general coding theorem is proved via a new nonasymptotic bound that uses stochastic likelihood coders and whose asymptotic analysis yields an extension of the Berger-Tung inner bound to the causal setting. The analysis of the Gaussian case is facilitated by reversing the channels of the observers.

关键词： CEO problem Berger-Tung bound distributed source coding causal rate-distortion theory Gauss-Markov source LQG control directed information

来源：评论

学校读者我要写书评

暂无评论

Energy-efficient data transmission technique for wireless sensor networks based on DSC and virtual MIMO

引用

ETRI JOURNAL 2020年第3期42卷 341-350页

作者： Singh, Manish Kumar Amin, Syed Intekhab KIET Grp Inst Ghaziabad India Jamia Millia Islamia New Delhi India

In a wireless sensor network (WSN), the data transmission technique based on the cooperative multiple-input multiple-output (CMIMO) scheme reduces the energy consumption of sensor nodes quite effectively by utilizing the space-time block coding scheme. However, in networks with high node density, the scheme is ineffective due to the high degree of correlated data. Therefore, to enhance the energy efficiency in high node density WSNs, we implemented the distributed source coding (DSC) with the virtual multiple-input multiple-output (MIMO) data transmission technique in the WSNs. The DSC-MIMO first compresses redundant source data using the DSC and then sends it to a virtual MIMO link. The results reveal that, in the DSC-MIMO scheme, energy consumption is lower than that in the CMIMO technique;it is also lower in the DSC single-input single-output (SISO) scheme, compared to that in the SISO technique at various code rates, compression rates, and training overhead factors. The results also indicate that the energy consumption per bit is directly proportional to the velocity and training overhead factor in all the energy saving schemes.

关键词： cluster head CMIMO distributed source coding DSC-MIMO sensor nodes wireless sensor network

来源：评论

学校读者我要写书评

暂无评论

An efficient SF-ISF approach for the Slepian-Wolf source coding problem

引用

EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING 2005年第6期2005卷 961-971页

作者： Tu, ZY Li, J Blum, RS Lehigh Univ Dept Elect & Comp Engn Bethlehem PA 18105 USA

A simple but powerful scheme exploiting the binning concept for asymmetric lossless distributed source coding is proposed. The novelty in the proposed scheme is the introduction of a syndrome former (SF) in the source encoder and an inverse syndrome former (ISF) in the source decoder to efficiently exploit an existing linear channel code without the need to modify the code structure or the decoding strategy. For most channel codes, the construction of SF-ISF pairs is a light task. For parallelly and serially concatenated codes and particularly parallel and serial turbo codes where this appears less obvious, an efficient way for constructing linear complexity SF-ISF pairs is demonstrated. It is shown that the proposed SF-ISF approach is simple, provenly optimal, and generally applicable to any linear channel code. Simulation using conventional and asymmetric turbo codes demonstrates a compression rate that is only 0.06 bit/symbol from the theoretical limit, which is among the best results reported so far.

关键词： distributed source coding compression with side information at the decoder Slepian-Wolf coding code binning serially concatenated convolutional codes parallelly concatenated convolutional codes

来源：评论

学校读者我要写书评

暂无评论

Information Rates of Densely Sampled Data: distributed Vector Quantization and Scalar Quantization With Transforms for Gaussian sources

引用

IEEE TRANSACTIONS ON INFORMATION THEORY 2013年第9期59卷 5641-5664页

作者： Neuhoff, David L. Pradhan, S. Sandeep Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA

This paper establishes rates attainable by several lossy schemes for coding a continuous parameter source to a specified mean-squared-error distortion based on sampling at asymptotically large rates. First, a densely sampled, spatiotemporal, stationary Gaussian source is distributively encoded. The Berger-Tung bound to the distributed rate-distortion function and three convergence theorems are used to obtain an upper bound, expressed in terms of the source spectral density, to the smallest attainable rate at asymptotically large sampling rates. The bound is tighter than that recently obtained by Kashyap et al. Both indicate that with ideal distributed lossy coding, dense sensor networks can efficiently sense and convey a field, in contrast to the negative result obtained by Marco et al. for encoders based on scalar quantization and Slepian-Wolf distributed lossless coding. The second scheme is transform coding with scalar coefficient quantization. A new generalized transform coding analysis, as well as the aforementioned convergence theorems, is used to find the smallest attainable rate at asymptotically large sampling rates in terms of the source spectral density and the operational rate-distortion function of the family of quantizers, which in contrast to previous analyses need not be convex. The result shows that when a transform is used, scalar quantization need not cause the poor performance found by Marco et al. As a corollary, the final result pursues an approach, originally proposed by Berger, to show that the inverse water-pouring formula for the rate-distortion function can be attained at high sampling rates by transform coding with ideal vector quantization to encode the coefficients. Also established in the paper are relations between operational rate-distortion and distortion-rate functions for a continuous parameter source and those for the discrete parameter source that results from sampling.

关键词： Continuous-time source coding distributed source coding lossy source coding oversampling rate-distortion theory transform coding

来源：评论

学校读者我要写书评

暂无评论

The distributed Karhunen-Loeve transform

引用

IEEE TRANSACTIONS ON INFORMATION THEORY 2006年第12期52卷 5177-5196页

作者： Gastpar, Michael Dragotti, Pier Luigi Vetterli, Martin Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA Univ London Imperial Coll Sci Technol & Med Dept Elect & Elect Engn London SW7 2BT England Ecole Polytech Fed Lausanne Swiss Fed Inst Technol Inst Commun Syst CH-1015 Lausanne Switzerland

The Karhunen-Loeve transform (KLT) is a key element of many signal processing and communication tasks. Many recent applications involve distributed signal processing, where it is not generally possible to apply the KLT to the entire signal;rather, the KLT must be approximated in a distributed fashion. This paper investigates such distributed approaches to the KLT, where several distributed terminals observe disjoint subsets of a random vector. We introduce several versions of the distributed KLT. First, a local KLT is introduced, which is the optimal solution for a given terminal, assuming all else is fixed. This local KLT is different and in general improves upon the marginal KLT which simply ignores other terminals. Both optimal approximation and compression using this local KLT are derived. Two important special cases are studied in detail, namely, the partial observation KLT which has access to a subset of variables, but aims at reconstructing them all, and the conditional KLT which has access to side information at the decoder. We focus on the jointly Gaussian case, with known correlation structure, and on approximation and compression problems. Then, the distributed KLT is addressed by considering local KLTs in turn at the various terminals, leading to an iterative algorithm which is locally convergent, sometimes reaching a global optimum, depending on the overall correlation structure. For compression, it is shown that the classical distributed source coding techniques admit a natural transform coding interpretation, the transform being the distributed KLT. Examples throughout illustrate the performance of the proposed distributed KLT. This distributed transform has potential applications in sensor networks, distributed image databases, hyper-spectral imagery, and data fusion.

关键词： distributed source coding distributed transforms rate-distortion function principal components analysis side information transform coding

来源：评论

学校读者我要写书评

暂无评论

Modeling the lossy transmission of correlated sources in multiple access fading channels

引用

PHYSICAL COMMUNICATION 2017年第Sep.期24卷 34-45页

作者： Argyriou, Antonios Alay, Ozgu Palantas, Panagiotis Univ Thessaly Dept Elect & Comp Engn Volos 38221 Greece Simula Res Lab Networks Dept Oslo Norway

In this paper, we develop accurate distortion models for the lossy transmission of two correlated sources in a multiple access Rayleigh fading channel. We focus on a class of real-life communication systems, where the source and channel coders have already been designed separately and can only be configured during the system operation. We investigate three different source coding schemes: distributed source coding (DSC), layered source coding, and independent compression through quantization. With the later scheme the sources are jointly decoded with minimum mean square error (MMSE) estimation at the receiver. We also consider two different transmission schemes: Orthogonal transmissions and interfering transmissions decoded with a successive interference cancellation (SIC) decoder. Our final closed-form analytical models are used to determine the optimal combination of source coding and transmission schemes, as well as their optimal configuration. Hence, we exercise joint source and channel coding (JSCC) by optimizing the system configuration. Through simulations, we first validate the analytical model and illustrate the performance of different schemes. Finally, we demonstrate the JSCC gains achieved by our system. (C) 2017 Elsevier B.V. All rights reserved.

来源：评论

学校读者我要写书评

暂无评论

distributed Compression for Condition Monitoring of Wind Farms

引用

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2013年第1期4卷 174-181页

作者： Stankovic, Vladimir Stankovic, Lina Wang, Shuang Cheng, Samuel Univ Strathclyde Dept Elect & Elect Engn Glasgow G1 1XW Lanark Scotland Univ Oklahoma Sch Elect & Comp Engn Tulsa OK 74135 USA

A good understanding of individual and collective wind farm operation is necessary for improving the overall performance of the wind farm "grid," as well as estimating in real time the amount of energy that can be generated for effectively managing demand and supply over the smart grid. This paper proposes a scheme for compressing wind speed measurements exploiting both temporal and spatial correlation between the readings via distributed source coding. The proposed scheme relies on a correlation model based on true measurements. Two compression schemes are proposed, both of low encoding complexity, as well as a particle-filtering-based belief propagation decoder that adaptively estimates the nonstationary noise of the correlation model. Simulation results using realistic models show significant performance improvements compared to the scheme that does not dynamically refine correlation.

关键词： Adaptive decoding distributed compression distributed source coding wind farms

来源：评论

学校读者我要写书评

暂无评论

distributed Arithmetic coding for the Slepian-Wolf Problem

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2009年第6期57卷 2245-2257页

作者： Grangetto, Marco Magli, Enrico Olmo, Gabriella Univ Turin Dipartimento Informat I-10149 Turin Italy Politecn Torino Dipartimento Elettron I-10129 Turin Italy

distributed source coding schemes are typically based on the use of channels codes as source codes. In this paper we propose a new paradigm, named "distributed arithmetic coding," which extends arithmetic codes to the distributed case employing sequential decoding aided by the side information. In particular, we introduce a distributed binary arithmetic coder for the Slepian-Wolf coding problem, along with a joint decoder. The proposed scheme can be applied to two sources in both the asymmetric mode, wherein one source acts as side information, and the symmetric mode, wherein both sources are coded with ambiguity, at any combination of achievable rates. distributed arithmetic coding provides several advantages over existing Slepian-Wolf coders, especially good performance at small block lengths, and the ability to incorporate arbitrary source models in the encoding process, e.g., context-based statistical models, in much the same way as a classical arithmetic coder. We have compared the performance of distributed arithmetic coding with turbo codes and tow-density parity-check codes, and found that the proposed approach is very competitive.

关键词： Arithmetic coding compression distributed source coding LDPC codes Slepian-Wolf coding turbo codes Wyner-Ziv coding

来源：评论

学校读者我要写书评

暂无评论

Precoding and decoding paradigms for distributed vector data compression

引用

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2007年第4期55卷 1445-1460页

作者： Vosoughi, Azadeh Scaglione, Anna Univ Rochester Dept Elect & Comp Engn Rochester NY 14627 USA Cornell Univ Sch Elect & Comp Engn Ithaca NY 14853 USA

In this paper, we consider the problem of lossy coding of correlated vector sources with uncoded side information available at the decoder. In particular, we consider lossy coding of vector source x is an element of R-N which is correlated with vector source y is an element of R-N, known at the decoder. We propose two compression schemes, namely, distributed adaptive compression (DAC) and distributed universal compression (DUC) schemes. The DAC algorithm is inspired by the optimal solution for Gaussian sources and requires computation of the conditional Karhunen-Love transform (CKLT) of the data at the encoder. The DUC algorithm, however, does not require knowledge of the CKLT at the encoder. The DUC algorithms are based on the approximation of the correlation model between the sources V and x through a linear model y = Hx + n in which H is a matrix and n is a random vector and independent of x. This model can be viewed as a fictitious communication channel with input x and output V. Utilizing channel equalization at the receiver, we convert the original vector source coding problem into a set of manageable scalar source coding problems. Furthermore, inspired by bit loading strategies employed in wireless communication systems, we propose for both compression schemes a rate allocation policy which minimizes the decoding error rate under a total rate constraint. Equalization and bit loading are paired with a quantization scheme for each vector source entry (a slightly simplified version of the so called DISCUS scheme). The merits of our work are as follows: 1) it provides a simple, yet optimized, implementation of Wyner-Ziv quantizers for correlated vector sources, by using the insight gained in the design of communication systems;2) it provides encoding schemes that, with or without the knowledge of the correlation model at the encoder, enjoy distributed compression gains.

关键词： binnig Conditional Karhunen-Loeve transform (CKLT) correlated vector sources coset construction distributed source coding equalization Gaussian sources lossy coding pre-coding quantization rate allocation source coding with side information transform coding Wyner-Ziv encoders

来源：评论

学校读者我要写书评

暂无评论

Wyner-Ziv coding Based on Multidimensional Nested Lattices

引用

IEEE TRANSACTIONS ON COMMUNICATIONS 2012年第5期60卷 1328-1335页

作者： Ling, Cong Gao, Su Belfiore, Jean-Claude Univ London Imperial Coll Sci Technol & Med Dept Elect & Elect Engn London SW7 2AZ England Telecom ParisTech Dept Commun & Elect Paris France

distributed source coding addresses the compression of correlated sources without communication links among them. This paper is concerned with the Wyner-Ziv problem: coding of an information source with side information available only at the decoder in the form of a noisy version of the source. Both the problems of theoretical analysis and code design are addressed in the framework of multi-dimensional nested lattice coding. For theoretical analysis, accurate computation of the rate-distortion function is given under the high-resolution assumption, and a new upper bound using the derivative of the theta series is derived. For practical code design, several low-complexity techniques are proposed. Compared to the existing Slepian-Wolf coded nested quantization for Wyner-Ziv coding based on one or two-dimensional lattices, our proposed multi-dimensional lattice coding can offer better performance at arguably lower complexity, since it does not require the second stage of Slepian-Wolf coding.

关键词： distributed source coding multi-dimensional lattices nested lattices rate-distortion function Wyner-Ziv coding

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：