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distributed estimation using reduced-dimensionality sensor observations

IEEE TRANSACTIONS ON SIGNAL PROCESSING 2007年第8期55卷 4284-4299页

作者： Schizas, Ioannis D. Giannakis, Georgios B. Luo, Zhi-Quan Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA

We derive linear estimators of stationary random signals based on reduced-dimensionality observations collected at distributed sensors and communicated to a fusion center over wireless links. Dimensionality reduction compresses sensor data to meet low-power and bandwidth constraints, while linearity in compression and estimation are well motivated by the limited computing capabilities wireless sensor networks are envisioned to operate with, and by the desire to estimate random signals from observations with unknown probability density functions. In the absence of fading and fusion center noise (ideal links), we cast this intertwined compression-estimation problem in a canonical correlation analysis framework and derive closed-form mean-square error (MSE) optimal estimators along with coordinate descent suboptimal alternatives that guarantee convergence at least to a stationary point. Likewise, we develop estimators based on reduced-dimensionality sensor observations in the presence of fading and additive noise at the fusion center (nonideal links). Performance analysis and corroborating simulations demonstrate the merits of the novel distributed estimators relative to existing alternatives.

关键词： canonical correlation analysis (CCA) distributed compression distributed estimation nonlinear optimization wireless sensor networks (WSNs)

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Recursive Implementation of the distributed Karhunen-Loeve Transform

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2010年第10期58卷 5320-5330页

作者： Amar, Alon Leshem, Amir Gastpar, Michael Delft Univ Technol Fac Elect Engn NL-2628 CD Delft Netherlands Bar Ilan Univ Sch Engn IL-52900 Ramat Gan Israel Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA

In the distributed linear source coding problem, a set of distributed sensors observe subsets of a data vector with noise, and provide the fusion center linearly encoded data. The goal is to determine the encoding matrix of each sensor such that the fusion center can reconstruct the entire data vector with minimum mean square error. The recently proposed local Karhunen-Loeve transform approach performs this task by optimally determining the encoding matrix of each sensor assuming the other matrices are fixed. This approach is implemented iteratively until convergence is reached. Herein, we propose a greedy algorithm. In each step, one of the encoding matrices is updated by appending an additional row. The algorithm selects in a greedy fashion a single sensor that provides the largest improvement in minimizing the mean square error. This algorithm terminates after a finite number of steps, that is, when all the encoding matrices reach their predefined encoded data size. We show that the algorithm can be implemented recursively, and compared to the iterative approach, the algorithm reduces the computational load from cubic dependency to quadratic dependency on the data size. This makes it a prime candidate for on-line and real-time implementations of the distributed Karhunen-Loeve transform. Simulation results suggest that the mean square error performance of the suggested algorithm is equivalent to the iterative approach.

关键词： distributed compression distributed Karhunen-Loeve transform distributed transforms principal component analysis source coding transform coding

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Interactive Nearest Lattice Point Search in a distributed Setting: Two Dimensions

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IEEE TRANSACTIONS ON COMMUNICATIONS 2022年第8期70卷 5128-5139页

作者： Vaishampayan, Vinay A. Bollauf, Maiara F. CUNY Coll Staten Isl Dept Elect Engn Staten Isl NY 10314 USA Simula UiB N-5006 Bergen Norway

The nearest lattice point problem in R-n is formulated in a distributed network with n nodes. The objective is to minimize the probability that an incorrect lattice point is found, subject to a constraint on inter-node communication. Algorithms with a single as well as an unbounded number of rounds of communication are considered for the case n = 2. For the algorithm with a single round, expressions are derived for the error probability as a function of the total number of communicated bits. We observe that the error exponent depends on the lattice structure and that zero error requires an infinite number of communicated bits. In contrast, with an infinite number of allowed communication rounds, the nearest lattice point can be determined without error with a finite average number of communicated bits and a finite average number of rounds of communication. In two dimensions, the hexagonal lattice, which is most efficient for communication and compression, is found to be the most expensive in terms of communication cost.

关键词： Lattices lattice quantization nearest lattice point problem communication complexity distributed function computation distributed compression

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Fountain Code Design for Data Multicast with Side Information

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2009年第10期8卷 5155-5165页

作者： Sejdinovic, Dino Piechocki, Robert J. Doufexi, Angela Ismail, Mohamed Univ Bristol Dept Elect & Elect Engn Ctr Commun Res Bristol Avon England Toshiba Res Europe Ltd Telecommun Res Lab Bristol Avon England

Fountain codes are a robust solution for data multi-casting to a large number of receivers which experience variable channel conditions and different packet loss rates. However, the standard fountain code design becomes inefficient if all receivers have access to some side information correlated with the source information. We focus our attention on the cases where the correlation of the source and side information can be modelled by a binary erasure channel (BEC) or by a binary input additive white Gaussian noise channel (BIAWGNC). We analyse the performance of fountain codes in data multicasting with side information for these cases, derive bounds on their performance and provide a fast and robust linear programming optimization framework for code parameters. We demonstrate that systematic Raptor code design can be employed as a possible solution to the problem at the cost of higher encoding/decoding complexity, as it reduces the side information scenario to a channel coding problem. However, our results also indicate that a simpler solution, non-systematic LT and Raptor codes, can be designed to perform close to the information theoretic bounds.

关键词： Fountain codes distributed compression joint source-channel coding side information

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Channel Simulation and Coded Source compression

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IEEE TRANSACTIONS ON INFORMATION THEORY 2016年第11期62卷 6609-6619页

作者： Hsieh, Min-Hsiu Watanabe, Shun Univ Technol Sydney Fac Engn & Informat Technol Ctr Quantum Computat & Intelligent Syst Ultimo NSW 2007 Australia Tokyo Univ Agr & Technol Dept Comp & Informat Sci Koganei Tokyo 1848588 Japan

Coded source compression, also known as source compression with helpers, has been a major variant of distributed source compression, but has hitherto received little attention in the quantum regime. This letter treats and solves the corresponding quantum coded source compression through an observation that connects coded source compression with channel simulation. First, we consider classical source coding with quantum side information, where the quantum side information is observed by a helper and sent to the decoder via a classical channel. We derive a single-letter characterization of the achievable rate region for this problem. The direct coding theorem of our result is proved via the measurement compression theory of Winter, a quantum-to-classical channel simulation. Our result reveals that a helper's scheme which separately conducts a measurement and a compression is suboptimal, and measurement compression seems necessary to achieve the optimal rate region. We then study coded source compression in the fully quantum regime, where two different scenarios are considered depending on the types of communication channels between the legitimate source and the receiver. We further allow entanglement assistance from the quantum helper in both scenarios. We characterize the involved quantum resources and derive single-letter expressions of the achievable rate region. The direct coding proofs are based on well-known quantum protocols, the quantum state merging protocol, and the fully quantum Slepian-Wolf protocol, together with the quantum reverse Shannon theorem.

关键词： Source coding channel simulation measurement compression quantum information distributed compression

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Achievability Performance Bounds for Integer-Forcing Source Coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2020年第3期66卷 1482-1496页

作者： Domanovitz, Elad Erez, Uri Tel Aviv Univ Dept Elect Engn Syst IL-6997801 Tel Aviv Israel

Integer-forcing source coding has been proposed as a low-complexity method for compression of distributed correlated Gaussian sources. In this scheme, each encoder quantizes its observation using the same fine lattice and reduces the result modulo a coarse lattice. Rather than directly recovering the individual quantized signals, the decoder first recovers a full-rank set of judiciously chosen integer linear combinations of the quantized signals, and then inverts it. It has been observed that the method works very well for "most" but not all source covariance matrices. The present work quantifies the measure of bad covariance matrices by studying the probability that integer-forcing source coding fails as a function of the allocated rate, where the probability is with respect to a random orthonormal transformation that is applied to the sources prior to quantization. For the important case where the signals to be compressed correspond to the antenna inputs of relays in an i.i.d. Rayleigh fading environment, this orthonormal transformation can be viewed as being performed by nature. The scheme is also studied in the context of a non-distributed system. Here, the goal is to arrive at a universal, yet practical, compression method using equal-rate quantizers with provable performance guarantees. The scheme is universal in the sense that the covariance matrix need only be learned at the decoder but not at the encoder. The goal is accomplished by replacing the random orthonormal transformation by transformations corresponding to number-theoretic space-time codes.

关键词： Source coding Covariance matrices Precoding Lattices Decoding Quantization (signal) Distortion distributed compression integer forcing unitary precoding

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

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2014年第3期13卷 1555-1567页

作者： Kang, Jinkyu Simeone, Osvaldo Kang, Joonhyuk Shamai (Shitz), Shlomo Korea Adv Inst Sci & Technol Dept Elect Engn Taejon 305701 South Korea New Jersey Inst Technol ECE Dept CWCSPR Newark NJ 07102 USA Technion Israel Inst Technol Dept Elect Engn IL-32000 Haifa Israel

In network MIMO cellular systems, subsets of base stations (BSs), or remote radio heads, are connected via backhaul links to central units (CUs) that perform joint encoding in the downlink and joint decoding in the uplink. Focusing on the uplink, an effective solution for the communication between BSs and the corresponding CU on the backhaul links is based on compressing and forwarding the baseband received signal from each BS. In the presence of ergodic fading, communicating the channel state information (CSI) from the BSs to the CU may require a sizable part of the backhaul capacity. In a prior work, this aspect was studied by assuming a Compress-Forward-Estimate (CFE) approach, whereby the BSs compress the training signal and CSI estimation takes place at the CU. In this work, instead, 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 choice is motivated by the information theoretic optimality of separate estimation and compression. Various ECF strategies are proposed that perform either separate or joint compression of estimated CSI and received signal. Moreover, the proposed strategies are combined with distributed source coding when considering multiple BSs. "Semi-coherent" strategies are also proposed that do not convey any CSI or training information on the backhaul links. Via numerical results, it is shown that a proper design of ECF strategies based on joint received signal and estimated CSI compression or of semi-coherent schemes leads to substantial performance gains compared to more conventional approaches based on non-coherent transmission or the CFE approach.

关键词： Uplink network MIMO distributed antenna systems limited backhaul imperfect CSI compress and forward distributed compression indirect compression cloud radio access

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distributed Adaptive Estimation of Node-Specific Signals in Wireless Sensor Networks With a Tree Topology

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2011年第5期59卷 2196-2210页

作者： Bertrand, Alexander Moonen, Marc Katholieke Univ Leuven Dept Elect Engn ESAT SCD SISTA B-3001 Leuven Belgium

We present a distributed adaptive node-specific signal estimation (DANSE) algorithm that operates in a wireless sensor network with a tree topology. The algorithm extends the DANSE algorithm for fully connected sensor networks, as described in previous work. It is argued why a tree topology is the natural choice if the network is not fully connected. If the node-specific desired signals share a common latent signal subspace, it is shown that the distributed algorithm converges to the same linear MMSE solutions as obtained with the centralized version of the algorithm. The computational load is then shared between the different nodes in the network, and nodes exchange only linear combinations of their sensor signal observations and data received fromtheir neighbors. Despite the low connectivity of the network and the multi-hop signal paths, the algorithm is fully scalable in terms of communication bandwidth and computational power. Two different cases are considered concerning the communication protocol between the nodes: point-to-point transmission and local broadcasting. The former assumes that there is a reserved communication link between node-pairs, whereas with the latter, nodes communicate the same data to all of their neighbors simultaneously. The convergence properties of the algorithm are demonstrated by means of numerical examples.

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

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Rate Region of the One-Help-Two Quadratic Gaussian Source-Coding Problem With Markovity

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IEEE TRANSACTIONS ON INFORMATION THEORY 2023年第3期69卷 2009-2032页

作者： Bilgen, Omer Wagner, Aaron B. Cornell Univ Sch Elect & Comp Engn Ithaca NY 14853 USA JPMorgan Asset Management London EC4Y 0JP England

We study the quadratic Gaussian one-help-two source-coding problem with Markovity, in which three encoders separately encode the components of a memoryless vector-Gaussian source that form a Markov chain and the central decoder aims to reproduce the first and the second components in the chain subject to individual mean-squared distortion constraints. We determine the rate region under a high-resolution assumption for the middle source.

关键词： Multiterminal source-coding distributed compression Gaussian sources one-help-two problem network information theory

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The Filtered Gaussian Primitive Diamond Channel

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IEEE TRANSACTIONS ON COMMUNICATIONS 2022年第5期70卷 3096-3109页

作者： Katz, Asif Peleg, Michael Shamai (Shitz), Shlomo Technion Israel Inst Technol Andrew & Erna Fac Elect & Comp Engn IL-3200003 Haifa Israel Technion Israel Inst Technol IL-3200003 Haifa Israel Rafael Ltd IL-3102102 Haifa Israel

We investigate a special case of diamond relay comprising Gaussian channels with an identical frequency response from the user to the relays, and with lossless fronthaul links with limited rate from the relays to the destination. We use the oblivious compress and forward (CF) scheme with with distributed compression, and a decode and forward (DF) scheme, where each relay decodes the whole message and sends half of the bits to the destination. It is proved that optimal CF-DF time-sharing scheme is advantageous over the CF-DF superposition scheme. We derive an achievable rate by using time-sharing between CF and DF. The optimal time-sharing proportion between CF and DF, and the power and rate allocations are different for each frequency and are fully determined.

关键词： Relays Diamond Time-frequency analysis Radio spectrum management Decoding Resource management Signal to noise ratio Diamond relay channel information bottleneck compress and forward decode and forward distributed compression

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