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共 463 条记录，以下是311-320 订阅

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Distributed UAV Beamforming Using Graph Recurrent Neural Networks

Distributed UAV Beamforming Using Graph Recurrent Neural Net...

引用

sensor array and multichannel signal processing workshop

作者： Wenqing Zheng Brian M. Sadler Fernando Gama Tianlong Chen Univ. of Texas at Austin Austin TX USA Univ. of Pennsylvania Philadelphia PA USA

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

In this paper we develop a novel learning-based approach for mobile distributed beamforming without channel state information. We consider narrowband beamforming between a mobile UAV group and a base station under limited feedback, and propose a graph recurrent neural network (GRNN) approach to leverage local collaboration among the UAVs. The GRNN method is shown to be robust to variations in UAV speeds and group heading, and scales with the UAV group size. We compare to codebook and binary feedback methods and show that better performance is achieved with the proposed GRNN method.

关键词： Training Base stations Tracking loops Recurrent neural networks array signal processing Autonomous aerial vehicles Picture archiving and communication systems

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ADMM for $\ell_{0}$ Factor Analysis

ADMM for $\ell_{0}$ Factor Analysis

引用

sensor array and multichannel signal processing workshop

作者： Linyang Wang Wanquan Liu Bin Zhu School of Intelligent Systems Engineering Sun Yat-sen University Shenzhen China

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Factor analysis is widely utilized for data dimensionality reduction. Its objective is to extract a low-rank plus sparse factor structure from the covariance matrix of the observed data. In this paper, we propose a nonconvex and nonsmooth optimization model to obtain the additive matrix decomposition based on the nuclear norm of the low-rank component, the $\ell_{0}$ norm of the sparse component, and the Kullback-Leibler divergence between the candidate covariance matrix and the sample covariance matrix. We present an ADMM algorithm to solve the optimization problem and demonstrate its effectiveness through experiments on both synthetic and real datasets.

关键词： Dimensionality reduction Optimization models Noise signal processing algorithms Estimation Numerical models Matrix decomposition

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Antenna array configurations for massive MIMO outdoor base stations

Antenna array configurations for massive MIMO outdoor base s...

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sensor array and multichannel signal processing workshop

作者： Xavier Artiga Julien Perruisseau-Carrier Ana I. Pérez-Neira Centre Tecnològic de Telecomunicacions de Catalunya (CTTC) Barcelona Spain Adaptive MicroNano Wave Systems Group Ecole Poly technique Federale de Lausanne (EPFL) Lausanne Switzerland

Massive MIMO predicts unprecedented capacity and energy efficiency improvements in future networks, by the use of base stations with hundreds of antennas. However the crucial question of determining suitable, or even optimal, antenna hardware solutions for deploying such a large number of antennas in constrained physical spaces is still open. Here we analyse the potential benefits of using compact arrays, dual-polarized arrays, and 2D arrays in outdoor scenarios using a realistic 3D spatial channel model and accurate antenna electromagnetic simulations. In particular we show that it is detrimental to reduce the distance between elements below λ/3. Actually, better performances can be achieved by increasing the number of antennas using dual polarization instead (if random polarization of user antennas is assumed). We also show that good performance can be achieved by using 2D arrays, but at the expense of an increased number of total elements when compared to horizontal linear arrays.

关键词： arrays Mutual coupling MIMO Antenna arrays signal to noise ratio Channel models

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ADMM-Based Outage Constrained MIMO-ISAC Hybrid Beamforming Design

ADMM-Based Outage Constrained MIMO-ISAC Hybrid Beamforming D...

引用

sensor array and multichannel signal processing workshop

作者： Hao Liang Bin Liao College of Electronics and Information Engineering Shenzhen University Shenzhen China State Key Laboratory of Radio Frequency Heterogeneous Integration Shenzhen University Shenzhen China

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

This paper considers the problem of robust hybrid beamforming design for multiple-input multiple-output (MIMO) integrated sensing and communications (ISAC) systems in the presence of channel state information (CSI) error. Specifically, the analog and digital hybrid beamformer at the transmitter is designed with imperfect CSI, through synthesizing a desired transmit power pattern for radar sensing under the outage probability constraints on the signal-to-interference-plus-noise ratio (SINR) of each user. The formulated nonconvex problem is addressed by taking advantage of the Cantelli's Inequality and the Alternating Direction Method of Multipliers (ADMM) frame- work, and deriving the solution of each subproblem involved in the algorithm. Numerical experiments are carried out to show the effectiveness and robustness of the proposed MIMO-ISAC hybrid beamforming design.

关键词： array signal processing Simulation signal processing algorithms Interference Probability Integrated sensing and communication Approximation algorithms

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Frequency-Switching Sparse arrays

Frequency-Switching Sparse Arrays

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sensor array and multichannel signal processing workshop

作者： Yimin D. Zhang Md. Waqeeb T. S. Chowdhury Department of Electrical and Computer Engineering Temple University Philadelphia PA USA

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

In this paper, we propose high-resolution target direction-of-arrival (DOA) estimation using frequency-switching sparse arrays which implement multi-frequency sparse arrays in a low-complexity manner. Unlike multi-frequency sparse arrays which require processing of wideband signals comprising multiple frequency components, the proposed frequency-switching sparse arrays only need to process a single-frequency component at any time instant, thereby eliminating such hurdles and significantly reducing the system complexity. A frequency-switching sparse array achieves the same number of degrees-of-freedom as a multi-frequency counterpart with comparable DOA estimation performance. Numerical results on the DOA estimation performance and Cramer- Rao bounds are provided to illustrate the effectiveness of the proposed frequency-switching sparse arrays.

关键词： Time-frequency analysis Direction-of-arrival estimation array signal processing Estimation Receivers Frequency estimation Frequency diversity

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Track - Before- Detect Labeled Multi - Bernoulli Filter for Multi- Target Bearing-Only Tracking using an Autonomous Underwater Vehicle

Track - Before- Detect Labeled Multi - Bernoulli Filter for ...

引用

sensor array and multichannel signal processing workshop

作者： Ce Zheng Yankun Chen Qisen Wang Xiang Li Sijian Liu Chao Dong Key Laboratory of Marine Environmental Survey Technology and Application Ministry of Natural Resources of the People's Republic of China Guangzhou China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai China College of Oceanography and Space Informatics China University of Petroleum (East China) Qingdao China

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

This paper considers an autonomous underwater vehicle (AUV) mounted with an array of sensors to detect the presence of multiple targets and estimate their relative locations. We propose a track-before-detect labeled multi-Bernoulli filter, which directly utilizes the signals received from the sensor array as the measurement in the form of a sample-covariance matrix (SCM). Tractable filtering equations are derived by using a change of variable and complex inverse-Wishart approximation. Simulation results demonstrate the improved performance of the proposed filter in challenge scenarios of low signal-to-noise ratio and multiple target crossing.

关键词： Autonomous underwater vehicles Target tracking array signal processing Filtering Simulation Mathematical models sensors

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COROID: A Crowdsourcing-based Companion Drones to Tackle Current and Future Pandemics

COROID: A Crowdsourcing-based Companion Drones to Tackle Cur...

引用

sensor array and multichannel signal processing workshop

作者： Ashish Rauniyar Desta Haileselassie Hagos Debesh Jha Jan Erik Hå kegå rd Sustainable Communication Technologies Group SINTEF Digital Norway Division of Software and Computer Systems KTH Royal Institute of Technology Sweden Department of Radiology Northwestern University USA

Due to the current COVID-19 virus, which has already been declared a pandemic by the World Health Or-ganization (WHO), we are witnessing the greatest pandemic of the decade. Millions of people are being infected, resulting in thousands of deaths every day across the globe. Even the world's best healthcare-providing countries could not handle the pandemic because of the strain of treating thousands of patients at a time. The count of infections and deaths is increasing at an alarming rate because of the spread of the virus. We believe that innovative technologies could help reduce pandemics to a certain extent until we find a definite solution from the medical field to handle and treat such pandemic situations. Technology innovation has the potential to introduce new technologies that could support people and society during these difficult times. Therefore, this paper proposes the idea of using drones as a companion to tackle current and future pandemics. Our COROID drone is based on the principle of crowdsourcing sensors data of the public's smart devices, which can correlate the reading of the infrared cameras equipped on COROID drones. To the best of our knowledge, this concept has yet to be investigated either as a concept or as a product. Therefore, we believe that the COROID drone is innovative and has a huge potential to tackle COVID-19 and future pandemics.

关键词： COVID-19 Crowdsourcing Technological innovation Pandemics Conferences Smart devices Intelligent sensors

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Sparse array and Precoding Design for Integrated Sensing and Communication Systems

Sparse Array and Precoding Design for Integrated Sensing and...

引用

sensor array and multichannel signal processing workshop

作者： R.S. Prasobh Sankar Sundeep Prabhakar Chepuri Indian Institute of Science Bengaluru Karnataka India

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

In this paper, we perform joint antenna selection and transmit pre-coder design for integrated sensing and communication (ISAC) systems to meet signal-to-interference-plus-noise-ratio (SINR) requirements at the users while being capable of identifying, i.e., estimating the direction of arrivals (DoAs), of certain number of sources. We first present a sufficient condition to ensure certain identifiability. Next, through a series of relaxations, we obtain a convex approximation to the combinatorial antenna selection and precoding problem, which we solve using off-the-shelf solvers. The proposed method offers comparable performance to ISAC systems with optimal antenna selection obtained through exhaustive search while significantly out-performing ISAC systems with arbitrarily selected active antennas.

关键词： Sufficient conditions Direction-of-arrival estimation array signal processing Transmitting antennas Interference Integrated sensing and communication Radar antennas

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An Efficient Optimization Framework for Learning General Signed Graphs From Smooth signals

An Efficient Optimization Framework for Learning General Sig...

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sensor array and multichannel signal processing workshop

作者： Shi-Yuk Fong Anthony Man-Cho So Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong SAR China Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong SAR China

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

Graph learning has been widely used in many fields to study the relationships between different entities in a dataset. We present an optimization framework based on the proximal alternating direction method of multipliers (pADMM) for learning general signed graphs from smooth signals. We show that our proposed pADMM enjoys global convergence and a local linear convergence rate. Then, we demonstrate the effectiveness of the proposed framework through numerical experiments on signed graphs. Our proposed framework provides a promising approach for learning general signed graphs from smooth signals and can be a valuable tool for data analysis and decision-making in various fields.

关键词： Data analysis array signal processing Conferences Decision making Optimization Convergence sensor arrays

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On Detecting Low-Pass Graph signals Under Partial Observations

On Detecting Low-Pass Graph Signals Under Partial Observatio...

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sensor array and multichannel signal processing workshop

作者： Hoang-Son Nguyen Hoi-To Wai Dept. of Computer Science & Engineering The Chinese University of Hong Kong Dept. of Systems Engineering & Engineering Management The Chinese University of Hong Kong

ISBN: (数字)9798350344813

ISBN: (纸本)9798350344820

The application of graph signal processing (GSP) on partially observed graph signals with missing nodes has gained attention recently. This is because processing data from large graphs are difficult, if not impossible due to the lack of availability of full observations. Many prior works have been developed using the assumption that the generated graph signals are smooth or low pass filtered. This paper treats a blind graph filter detection problem under this context. We propose a detector that certifies whether the partially observed graph signals are low pass filtered, without requiring the graph topology knowledge. As an example application, our detector leads to a pre-screening method to filter out non low pass signals and thus robustify the prior GSP algorithms. We also bound the sample complexity of our detector in terms of the class of filters, number of observed nodes, etc. Numerical experiments verify the efficacy of our method.

关键词： array signal processing Conferences Low-pass filters signal processing algorithms Detectors Filtering algorithms Complexity theory

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