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检索条件"任意字段=4th IEEE Sensor Array and Multichannel Signal Processing Workshop"

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A CLOSED-FORM SOLUTION FOR MULTILINEAR PARAFAC DECOMPOSITIONS

A CLOSED-FORM SOLUTION FOR MULTILINEAR PARAFAC DECOMPOSITION...

引用

2008 ieee sensor array and multichannel signal processing workshop

作者： Florian Roemer Martin Haardt Communications Research Laboratory Ilmenau University of Technology Ilmenau Germany

In this paper we study the R-way Parallel Factor Analysis (also referred to as R-way PARAFAC) problem. this branch of multi-way signal processing has received increased attention recently which is due to the versatility of the model as well as the identifiability results demonstrating its superiority to matrix-only (2-way) approaches. In R-way PARAFAC analysis, the goal is to decompose an R-dimensional tensor into a minimal sum of rank-1 terms. So far, there exist sub-optimal closed-form solutions as well as iterative techniques for finding these decompositions. However, the latter often require many iterations to converge. In this contribution we demonstrate that the R-way PARAFAC decomposition can be reduced to a set of simultaneous matrix diagonalization problems. Exploiting the structure of the R-dimensional problem, we obtain several estimates for each of the factors and present a "best matching" scheme to select the best estimate for each factor. By means of computer simulations we compare our closed-form solution to an iterative technique and demonstrate the enhanced robustness in critical scenarios.

关键词： Multidimensional signal processing Parameter estimation array signal processing

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MIMO radar signal processing for distributed phased arrays

MIMO radar signal processing for distributed phased arrays

引用

ieee International workshop on Computational Advances in Multi-sensor Adaptive processing (CAMSAP)

作者： Daniel R. Fuhrmann Department of Electrical and Computer Engineering Michigan Technological University Houghton MI USA

We explore transmit signaling and receive signal processing strategies for a notional MIMO radar system consisting of widely distributed phased arrays. the assumptions are that within a phased array, there is a fixed rigid geometry and perfect phase synchronization, and there is a single look at the target. In constrast, between phased arrays there is imperfect phase synchronization and multiple views of the target. the relative advantages and disadvantages of coherent and orthogonal signaling in such a model are explored through simulation.

关键词： Phased arrays MIMO radar array signal processing Synchronization Estimation MIMO

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Mismatch loss constrained instrumental variable filtering for GSM passive bistatic radar

Mismatch loss constrained instrumental variable filtering fo...

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sensor array and multichannel signal processing workshop

作者： Florian Bahlke Reda Zemmari Ulrich Nickel Marius Pesavento Sensor Data and Information Fusion Dept. Fraunhofer FKIE Wachtberg Germany Communication Systems Group University of Science Darmstadt Darmstadt Germany

In this paper we address the design and evaluation of a mismatched filter for application in GSM passive bistatic radar (PBR). We discuss various exisiting approaches for the filter design, which originate from active radar systems and have to be adapted for PBR. Our proposed method minimizes the L p -norm of the sidelobe level energies under an upper-bound constraint on the SNR loss relative to the matched filter. We show the suitibility of this approach for GSM based PBR and give a performance evaluation. Based on simulated and measured data, we show that the proposed filter can improve range resultion and target detection of the PBR system.

关键词： GSM Vectors signal to noise ratio Passive radar Conferences Bistatic radar

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MIMO Radar and Communications Spectrum Sharing: A Multiple-Access Perspective

MIMO Radar and Communications Spectrum Sharing: A Multiple-A...

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sensor array and multichannel signal processing workshop

作者： Yu Rong Alex R. Chiriyath Daniel W. Bliss Bliss Laboratory of Information Signals and Systems Arizona State University Tempe AZ

In this paper, we investigate the joint multiple-input multiple-output (MIMO) radar and communications system convergence problem and develop a joint radar-communications performance bound using the concept of estimation rate for radar system and data information rate for communications system. At the radar receiver, we propose a Successive Interference Cancellation (SIC) strategy to estimate radar parameters and decode communications signal simultaneously. While, at the MIMO communications transmitter, we propose a spectrum sharing scheme and show that the optimal communications performance can be achieved through a spectral and spatial waterfilling algorithm. In the end, we show that the Multiple-Access (MAC) performance bound outperforms the result from the spectrally isolated MIMO radar-communications system.

关键词： Radar Silicon carbide Estimation MIMO communication Radar signal processing

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Research directions for fourth generation wireless 10

Research directions for fourth generation wireless

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10th ieee International workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises (WET ICE 2001 )

作者： Woerner, B Howlader, M Virginia Tech Mobile & Portable Radio Res Grp Dept Elect & Comp Engn Blacksburg VA 24061 USA

ISBN: (纸本)0769512690

though taxonomies can be imprecise, wireless communications systems are frequently classified by generation. First generation wireless denotes voice-only analog cellular systems. Second generation wireless systems ushered in digital transmission technologies to meet the capacity demands of burgeoning voice services. the coming third generation differs from second generation systems more in the ability to integrate voice and data applications than in radical differences in transmission technology. though widespread deployment for third generation systems awaits widespread demand for wireless mobile data, we confidently predict that the Field of Dreams principle will continue to apply to the wireless industry. In this paper, we indulge in speculation on how these yet to be deployed systems may evolve, and the technologies that will be required to support the 4^th generation systems of the more distant future. © 2001 ieee.

关键词： Base stations Drives Electronic mail IP networks Mobile computing Postal services signal processing algorithms Telecommunication traffic Wireless networks Wireless sensor networks

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Nonlinear parameter estimation in statistical manifolds

Nonlinear parameter estimation in statistical manifolds

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sensor array and multichannel signal processing workshop

作者： Xuezhi Wang Yongqiang Cheng Bill Moran Department of Electrical and Electronic Engineering University of Melbourne Australia School of Electronic Science and Engineering National University of Defense Technology China Defense Science Institute University of Melbourne Australia

Many nonlinear parameter estimation problems can be described by the class of curved exponential families. the latter are fundamental concept in the framework of Information Geometry. this paper shows that when a closed-form statistical model is available the problem can be mapped onto the corresponding statistical manifolds via fixed parameterizations and thus solved optimally through a manifold gradient method. the solution process involves a dual projection which iteratively operates under the e-connection and m-connection in the flat manifolds with the coordinate systems in which the Cramér Rao Bound is attained. An example of tracking a moving target by two bearings-only sensors with location uncertainties is presented to demonstrate the efficiency and optimality of this manifold based method as well as the associated geometrical interpretation.

关键词： Manifolds Target tracking Estimation Uncertainty signal processing Conferences Educational institutions

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Multi-Efficiency Based Resource Allocation for Cognitive Radio Networks with Deep Learning

Multi-Efficiency Based Resource Allocation for Cognitive Rad...

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sensor array and multichannel signal processing workshop

作者： Miao Liu Tiecheng Song Lei Zhang Hikmet Sari Guan Gui National Mobile Communications Research Laboratory Southeast University Nanjing China School of Electrical and Information engineering Jiangsu University of Technology Changzhou China College of Telecommunication and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China

In this paper, a multi-efficiency based scheme is considered, for not only the energy efficiency (EE) and spectrum efficiency (SE) of the primary users (PUs) and the secondary users (SUs), but also the computing efficiency (CE) of the deep learning based RA algorithm in the cognitive radio networks (CRN). Considering the OFDMA based resource allocation (RA) problem for the underlaying SUs, a weighted sum of the secondary interference power is introduced as the objective to minimize. To solve the problem, a deep learning based reweighted message-passing algorithm (ReMPA) is proposed. Compared to the previous scheme and the traditional scheme, the simulation results show that the proposed scheme has effective improvement on both the SE and EE for PUs and SUs.

关键词： array signal processing sensor arrays Conferences Communications technology Resource management Machine learning

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Detection in analog sensor networks with a large scale antenna fusion center

Detection in analog sensor networks with a large scale anten...

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sensor array and multichannel signal processing workshop

作者： Feng Jiang Jie Chen A. Lee Swindlehurst Center for Pervasive Communications and Computing University of California at Irvine Irvine CA USA

We consider the distributed detection of a zero-mean Gaussian signal in an analog wireless sensor network with a fusion center (FC) configured with a large number of antennas. the transmission gains of the sensor nodes are optimized by minimizing the ratio of the log probability of detection (PD) and log probability of false alarm (PFA). We show that the problem is convex with respect to the squared norm of the transmission gains, and that a closed-form solution can be found using the Karush-Kuhn-Tucker conditions. Our results indicate that a constant PD can be maintained with decreasing sensor transmit gain provided that the number of antennas increases at the same rate. this is contrasted with the case of a singleantenna FC, where PD is monotonically decreasing with transmit gain. On the other hand, we show that when the transmit power is high, the single- and multi-antenna FC both asymptotically achieve the same PD upper bound.

关键词： Wireless sensor networks Upper bound Wireless communication Transmitting antennas Antenna measurements Fading

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Hybrid Particle Filtering Based on an Elitist Resampling Scheme

Hybrid Particle Filtering Based on an Elitist Resampling Sch...

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sensor array and multichannel signal processing workshop

作者： Mhd Modar Halimeh Christian Huemmer Andreas Brendel Walter Kellermann Multimedia Communications and Signal Processing Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany

In this paper, the elitist resampling particle filter (ERPF) is introduced. the ERPF is an approach to combine generic particle filters, i.e., the SIS and SIR particle filter, based on an evolutionary selection of particles, which introduces a longterm memory to the selected group of the particles. thereby, the ERPF aims at fusing the advantages, e.g., robustness and computational efficiency, and mitigating the drawbacks of each filter, e.g., degeneracy and sample impoverishment. Two variants of the ERPF are presented in this paper: the discrete ERPF (DERPF) and the continuous ERPF (CERPF), which to the authors' knowledge represent new forms of particle filters. the two proposed hybrids are compared to the corresponding original filters using two well-established benchmark models to illustrate that the evolutionary combinations provide a better estimation accuracy and exhibit an increased robustness against outliers.

关键词： Estimation Particle filters Robustness Sociology Statistics array signal processing

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Gaussian processes regressors for complex proper signals in digital communications

Gaussian processes regressors for complex proper signals in ...

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sensor array and multichannel signal processing workshop

作者： Rafael Boloix-Tortosa F. Javier Payán-Somet Juan José Murillo-Fuentes Dep. Teoría de la Señal y Comunicaciones Universidad de Sevilla Sevilla Spain

In this paper we develop the complex-valued version of the Gaussian processes for regression (GPR) for proper complex signals. this tool has proved to be useful in the nonlinear detection in digital communications in real valued models. GPRs can be cast as nonlinear MMSE where hyperparameters can be tuned optimizing a marginal likelihood (ML). this feature allows for a flexible kernel that can easily adapt either to a linear or nonlinear solution. We introduce the complex-valued form of the GPR, and develop it for the proper complex case. We also deal with the optimization of the ML. Some experiments included illustrate the good performance of the proposal.

关键词： Ground penetrating radar Vectors Gaussian processes Kernel Training signal processing Detectors

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