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A subspace tracking algorithm for separating partially overlapping data packets

A subspace tracking algorithm for separating partially overl...

引用

sensor array and multichannel signal processing workshop

作者： Mu Zhou Alle-Jan van der Veen Department of Electrical Engineering Delft University of Technology Delft Netherlands

Consider a narrowband wireless scenario where a terminal equipped with an antenna array is receiving short packets of equal length sent by users from different directions and transmitted at random time points. these packets can be fully or partially overlapping in time. the partially overlapping packets, called asynchronous interferences, make the scenario nonstationary and thus need to be suppressed. Previously, we proposed a subspace intersection algorithm based on signed URV decompositions (SURV) working on block data from one time slot to solve this problem but it needs many steps. In this paper, we propose a one-step subspace tracking algorithm providing competitive performance at a much lower computational complexity like updating a QR decomposition. this algorithm makes use of the tracking ability of SURV to track the orthonormal basis and the rank of the asynchronous interference-free subspace as its principal subspace tracking version through two subspaces with positive and negative signatures.

关键词： Interference signal to noise ratio Silicon Vectors signal processing algorithms Indexes Radar tracking

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Quantifying the advantages of joint processing in TDOA estimation

Quantifying the advantages of joint processing in TDOA estim...

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sensor array and multichannel signal processing workshop

作者： Arie Yeredor School of Electrical Engineering Tel Aviv University Tel-Aviv Israel

We address the problem of passive estimation of the Time-Difference of Arrival (TDOA) of an unknown, stochastic signal, at two sensors. the key question addressed here is whether additional sensors, receiving the same signal at various relative delays, can serve to improve the accuracy in estimating the TDOA of interest between the first two sensors (without exploiting any underlying parameterization, such as dependence on the transmitter's location). We derive the Cramér-Rao Lower Bound (CRLB) on the resulting joint estimation error in a model which possibly includes multipath reflections. We show analytically, that in a multipath-free scenario, at high to moderate signal to Noise Ratios, additional sensors do not offer any improvement in accuracy. However, we also demonstrate (numerically) that in the presence of multipath reflections (possibly received at all sensors), the additional sensors can indeed assist in estimating the TDOA of interest with improved accuracy.

关键词： Delay signal to noise ratio Accuracy Vectors Estimation error

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Effective rate analysis of MISO Rician fading channels

Effective rate analysis of MISO Rician fading channels

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sensor array and multichannel signal processing workshop

作者： Michail Matthaiou George C. Alexandropoulos Hien Quoc Ngo Erik G. Larsson Department of Signals and Systems Chalmers University of Technology Gothenburg Sweden Broadband Wireless and Sensor Networks Group Athens Information Technology Center Athens Greece Department of Electrical Engineering Linköping University Linkoping Sweden

the delay constraints imposed by future wireless applications require a suitable metric for assessing their impact on the overall system performance. Since the classical Shannon's ergodic capacity fails to do so, the so-called effective rate was recently established as a rigorous alternative. Yet, most prior relevant works have considered only the typical case of Rayleigh fading which allows for tractable manipulations. In this paper, we relax this assumption by considering the more general Rician fading model for multiple-input single-output (MISO) systems. A new, analytical expression for the exact effective rate is derived, along with tractable expressions for the key parameters dictating the effective rate performance in the high and low signal-to-noise (SNR) regimes.

关键词： Rician channels Delay signal to noise ratio Quality of service Wideband Rayleigh channels

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Dictionary based reconstruction and classification of randomly sampled sensor network data

Dictionary based reconstruction and classification of random...

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sensor array and multichannel signal processing workshop

作者： Grigorios Tsagkatakis Panagiotis Tsakalides Institute of Computer Science (ICS) Foundation for Research and Technology Hellas Crete Greece Department of Computer Science University of Crete Heraklion Crete Greece

In this paper, we propose a method for recovering and classifying WSN data while minimizing the number of samples that need to be acquired, processed, and transmitted. the problem is formulated according to the recently proposed framework of Matrix Completion (MC), which asserts that a low rank matrix can be recovered from a small number of randomly sampled entries. the application of MC in WSN data is motivated by the assumption that sensory data exhibit intra-sensor correlations and that these data can be represented using known examples. We formulate the problem as that of recovering the low rank measurement matrix by encoding the contributions of known examples, the dictionary elements, for reconstructing and classifying the data. Experimental results using artificial data suggest that the proposed scheme is able to accurately reconstruct and classify the sensory data from a small number of measurements.

关键词： Wireless sensor networks Dictionaries Correlation Noise Accuracy Minimization Noise measurement

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Low-overhead cooperative beamforming under imperfect quantized SNR of source-to-relay links

Low-overhead cooperative beamforming under imperfect quantiz...

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sensor array and multichannel signal processing workshop

作者： Jwo-Yuh Wu Chung-Hsuan Hu Tsang-Yi Wang Department of Electrical Engineering National Chiao Tung University Hsinchu Taiwan Institute of Communications Engineering National Sun Yat-sen University Kaohsiung Taiwan

ISBN: (纸本)9781467310703

We consider a cooperative beamforming system with the amplify-and-forward protocol. To reduce the signaling overhead, each relay quantizes the SNR of the source-to-relay (S-R) link into one bit, which is then transmitted through a binary symmetric channel (BSC) with a known crossover probability to the destination. Given the set of the error-corrupted one-bit messages received at the destination, the beamforming design criterion is the maximization of the expected receive SNR, averaged over the conditional bit-flipping distributions of BSCs. We derive an analytic expression for the considered SNR metric, which is a complicated function of the beamforming weights. To facilitate analysis, we further derive a tractable lower bound for the conditional average SNR. By conducting maximization with respect to this lower bound, a closed-form sub-optimal beamformer can be obtained as a solution to a generalized eigenvalue problem. Computer simulations are used to illustrate the performance of the proposed scheme.

关键词： signal to noise ratio array signal processing Relays Wireless sensor networks Protocols Measurement Computer simulation

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Enhancing WSN-based indoor positioning and tracking through RFID technology

Enhancing WSN-based indoor positioning and tracking through ...

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2012 4th International EURASIP workshop on RFID Technology, RFID 2012

作者： Xiong, Zhoubing Song, Zhen Yu Scalera, Andrea Sottile, Francesco Tomasi, Riccardo Spirito, Maurizio A. DET Politecnico di Torino Torino Italy Istituto Superiore Mario Boella PerT Area Torino Italy

ISBN: (纸本)9780769548135

Joint utilization of Wireless sensor Networks (WSNs) and Radio Frequency Identification (RFID) technologies is gathering increasing attention within the Internet of things (IoT) community due to the potential of providing pervasive context-aware applications with advantages from both worlds. While WSN system can in fact provide more sophisticated sensing, communication and processing capabilities, the possibility to passively perform detection of tags and the use of unique RFID identifiers provides IoT systems with several advantages, especially concerning maintenance;such advantages are considered especially beneficial in large-scale scenarios where thousands of nodes must be simultaneously deployed over wide areas. WSN-RFID convergence is considered especially promising in context-aware systems with indoor positioning capabilities, where data from already deployed WSN and RFID systems can be opportunistically exploited to refine and enhance collected data with position information. this paper discusses and evaluates a hybrid system where WSN and RFID technology have been integrated to support an indoor positioning service, feeding position information into a general-purpose IoT environment. Performance of the proposed system is evaluated by means of simulations and a small-scale experimental set-up. the performed analysis suggest that joint use of RFID and WSN can increase the robustness and accuracy of indoor positioning systems also in harsh propagation conditions. © 2012 ieee.

关键词： Wireless sensor networks

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Expected likelihood approach for covariance matrix estimation: Complex angular central Gaussian case

Expected likelihood approach for covariance matrix estimatio...

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sensor array and multichannel signal processing workshop

作者： Yuri I. Abramovich Ben A. Johnson WR Systems VA Lockheed Martin IS&GS Littleton

We consider the problem of covariance matrix estimation for strongly non-homogeneous data (clutter), modelled as spherically invariant complex random vectors. When normalized, such data are described by a complex angular Gaussian distribution. For a number of independent identically distributed (i.i.d.) samples with this distribution, we introduce the likelihood ratio and demonstrate that for the true covariance matrix, this LR has a p.d.f. which does not depend on the true matrix itself, but rather just its dimension and sample support. this “scenario-invariance” is used to select regularizing parameters that reduce the LR of the MLE estimate to a level statistically equal to the likelihood of the true covariance matrix. We apply this approach to select the loading factor in fixed point loaded covariance matrix estimates, and the order in the fixed point time-varying auto regressive (TVAR) covariance matrix estimate.

关键词： Covariance matrix Maximum likelihood estimation Vectors signal processing Data models Loading

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thwarting traffic analysis: A signal processing perspective

Thwarting traffic analysis: A signal processing perspective

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sensor array and multichannel signal processing workshop

作者： Abhishek Mishra Parv Venkitasubramaniam ECE Department Lehigh University USA

Traffic analysis, where eavesdroppers retrieve networking information such as source-destination pairs and paths of data flow, severely compromises user privacy and can equip an adversary to launch more powerful network attacks. Anonymous communication, where users exchange information without revealing the communicating parties is essential in any data network. Chaum Mixing, where relay nodes or proxy servers use cryptographic and batching strategies to mask source identities, is a well technique to provide anonymous communication on the Internet. the mathematical analysis of Chaum mixes and the design of mixing strategies have utilized an information theoretic measure of anonymity based on Shannon entropy. In this work, a statistical signal processing framework is proposed to study optimal mixing strategies and the achievable anonymity. Using the detection time of an adversary as a metric, the maximum achievable anonymity of a mix is characterized as a function of its available memory and the allowed rate of dummy transmissions. It is shown that, in the absence of dummy transmissions, the maximum allowable time for anonymous transmission increases quadratically with the buffer size, and for a fixed buffer size, the system approaches perfect unobservability at a rate inversely proportional to the rate of dummy transmissions.

关键词： Conferences Privacy Delay signal processing Internet

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Decentralized data processing and management in Smart Grid via gossiping

Decentralized data processing and management in Smart Grid v...

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sensor array and multichannel signal processing workshop

作者： Xiao Li Zhifang Wang Anna Scaglione Dept. of Electrical and Computer Engineering University of California Davis CA USA

In this paper, we propose a model for a peer-to-peer database system architecture where each server is aware of the power system state vector, and that can provide a scalable architecture for the Smart Grid. the key new component is a decentralized gossip-based state estimation (G-SE) algorithm included as a stored database procedure, which constantly updates via network diffusion, the global state information vector in each server of the distributed database system (DDBS). In addition to provide global situation awareness, state aware DDBS can attain communication and storage efficiency first, by using the temporal and spatial correlation of the state to compress it and, second, by storing the state as side information to store measurement residuals. thanks to the G-SE primitive DDBS are more resilient to network attaks, can reduce network usage and streamline query processing for Smart Grid applications.

关键词： State estimation Smart grids Database systems Servers Vectors

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On the consistency of likelihood penalization methods in large sensor networks

On the consistency of likelihood penalization methods in lar...

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sensor array and multichannel signal processing workshop

作者： Pascal Vallet Philippe Loubaton Xavier Mestre Laboratoire dinformatique Gaspard Monge Marne-la-Vallee France Centre Tecnològic de Telecomunicacions de Catalunya Castelldefels Barcelona Spain

this paper is devoted to the problem of source detection with large sensor networks, in a context where the number of available samples N and the number of antennas M are of the same order of magnitude. We focus here on the popular likelihood penalization (LP) methods, such as Minimum Description Length (MDL) or Akaike Information Criterion (AIC). Such methods have been widely studied in the context where N >;>; M, and in particular the consistency of the MDL and the inconsistency of the AIC estimator were established in the asymptotic regime where N → ∞ while M remains constant. We propose here an analysis in the asymptotic regime where M;N both converge to ∞ at the same rate, and using results from random matrix theory, we establish conditions on the penalty term to ensure consistency of LP methods in this latter regime. As a consequence, we deduce that the MDL method is always inconsistent while the AIC method can be consistent in certain situations.

关键词： Manganese

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