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检索条件"任意字段=2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing"

共 109 条记录，以下是1-10 订阅

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Power-Saving Design for Holographic Metasurface Enabled NOMA Communications 9

Power-Saving Design for Holographic Metasurface Enabled NOMA...

引用

9th ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Sun, Zeyu Jing, Yindi Univ Alberta Dept Elect & Comp Engn Edmonton AB T6G 2M7 Canada

ISBN: (纸本)9798350344523

In this work the downlink non-orthogonal multiple access (NOMA) communications conducted by a holographic metasurface (HMTS) based transmitter with a single RF chain is investigated. The required transmit power for the transmitter to maintain the quality of service (QoS) of all users is derived. And two holographic beamforming schemes aiming at minimizing the required transmit power are developed. The first design is based on the semi-definite relaxation (SDR) of the required transmit power minimization problem while the second design is based on the optimal partitioning of the HMTS. Numerical results are provided to show the superiority of our proposed schemes.

关键词： Holographic metasurface (HMTS) non-orthogonal multiple access (NOMA) beamforming

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Kalman filter for dynamic imaging based on complex empirical covariances 9

Kalman filter for dynamic imaging based on complex empirical...

引用

9th ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Arab, Nawel Cano, Cyril Vin, Isabelle El Korso, Mohammed Nabil Chaumette, Eric Larzabal, Pascal Univ Paris Saclay SATIE ENS Paris Saclay F-91190 Gif Sur Yvette France Univ Toulouse ISAE SUPAERO F-31000 Toulouse France Univ Paris Saclay CentraleSupelec L2S F-91190 Gif Sur Yvette France

ISBN: (纸本)9798350344523

Kalman filter (KF) is a priori unsuitable for the estimation from sample covariance matrices as they cannot be formulated analytically as a function of state parameters to be estimated. In this work, we propose a novel KF adapted to sample covariance matrices under the unconditional signal model. It is evaluated on simulated data representative of a dynamic radio astronomy framework, considering multiple uncorrelated sources and Gaussian noise. The results show that our method is capable of effectively tracking moving sources in complex scenes with greater accuracy than a KF regularized in a standard way, i.e., without proper formalization of the noise model.

关键词： Estimation Kalman filter Visibility matrix Radio astronomy

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Compact Order Polynomial Singular Value Decomposition of a Matrix of Analytic Functions 9

Compact Order Polynomial Singular Value Decomposition of a M...

引用

9th ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Bakhit, Mohammed A. Khattak, Faizan A. Proudler, Ian K. Weiss, Stephan Rice, Garrey W. Univ Strathclyde Dept Elect & Elect Engn Glasgow G1 1XW Scotland MathWorks 180 West George St Glasgow G2 2NR Scotland

ISBN: (纸本)9798350344523

This paper presents a novel method for calculating a compact order singular value decomposition (SVD) of polynomial matrices, building upon the recently proven existence of an analytic SVD for analytic, non-multiplexed polynomial matrices. The proposed method calculates a conventional SVD in sample points on the unit circle, and then applies phase smoothing Algorithms to establish phase-coherence between adjacent frequency bins. This results in the extraction of compact order singular values and their corresponding singular vectors. The method is evaluated through experiments conducted on an ensemble of randomised polynomial matrices, demonstrating its superior performance in terms of higher decomposition accuracy andlower polynomial order compared to state-of-the-art techniques.

关键词： Singular value decomposition

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Joint Sparse Estimation with Cardinality Constraint via Mixed-Integer Semidefinite Programming 9

Joint Sparse Estimation with Cardinality Constraint via Mixe...

引用

9th ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Liu, Tianyi Matter, Frederic Sorg, Alexander Pfetsch, Marc E. Haardt, Martin Pesavento, Marius Tech Univ Darmstadt Commun Syst Grp Darmstadt Germany Tech Univ Darmstadt Res Grp Optimizat Darmstadt Germany Ilmenau Univ Technol Commun Res Lab Ilmenau Germany

ISBN: (纸本)9798350344523

The multiple measurement vectors (MMV) problem refers to the joint estimation of multiple signal realizations where the signal samples share a common sparse support over a known dictionary, which is a fundamental challenge in various applications in signal processing, e.g., direction-ofarrival (DOA) estimation. We consider the maximum a posteriori (MAP) estimation of an MMV problem, which is classically formulated as a regularized least-squares (LS) problem with an l(2,0)-norm constraint and derive an equivalent mixed-integer semidefinite program (MISDP) reformulation, which can be solved by state-of-the-art numerical MISDP solvers at an affordable computation time. Numerical simulations in the context of DOA estimation demonstrate the improved error performance of our proposed method in comparison to several popular DOA estimation methods.

关键词： DOA estimation multiple measurement vectors joint sparsity l(2,0)-mixed-norm constraint mixed-integer semidefinite program maximum a posteriori estimation

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RIShield: Enabling Electromagnetic Blackout in Radiation-Sensitive Environments 9

RIShield: Enabling Electromagnetic Blackout in Radiation-Sen...

引用

9th ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Encinas-Lago, G. Rossanese, M. Sciancalepore, V. Di Renzo, Marco Costa-Perez, Xavier NEC Labs Europe GmbH Heidelberg Germany Univ Paris Saclay CNRS Cent Supelec Gif Sur Yvette France I2CAT Fdn Barcelona Spain ICREA Barcelona Spain

ISBN: (纸本)9798350344523

Reconfigurable Intelligent Surfaces (RIS) have emerged as a disruptive technology with the potential to revolutionize wireless communication systems. In this paper, we present RIShield, a novel application of RIS technology specifically designed for radiation-sensitive environments. The aim of RIShield is to enable electromagnetic blackouts, preventing radiation leakage from target areas. We propose a comprehensive framework for RIShield deployment, considering the unique challenges and requirements of radiation-sensitive environments. By strategically positioning RIS panels, we create an intelligent shielding mechanism that selectively absorbs and reflects electromagnetic waves, effectively blocking radiation transmission. To achieve optimal performance, we model the corresponding channel and design a dynamic control that adjusts the RIS configuration based on real-time radiation monitoring. By leveraging the principles of reconfiguration and intelligent control, RIShield ensures adaptive and efficient protection while minimizing signal degradation. Through full-wave and ray-tracing simulations, we demonstrate the effectiveness of RIShield in achieving significant electromagnetic attenuation. Our results highlight the potential of RIS technology to address critical concerns in radiation sensitive environments, paving the way for safer and more secure operations in industries such as healthcare, nuclear facilities, and defense.

关键词： Electromagnetic shielding

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Pandemic intensity estimation from Stochastic Approximation-based algorithms 9

Pandemic intensity estimation from Stochastic Approximation-...

引用

9th ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Abry, Patrice Chevallier, Juliette Fort, Gersende Pascal, Barbara ENS Lyon CNRS Lab Phys Lyon France Univ Toulouse INSA Toulous UMR 5219 IMT Toulouse France Univ Toulouse CNRS UMR 5219 IMT Toulouse France Nantes Univ ECN CNRS LS2N Nantes France

ISBN: (纸本)9798350344523

Pandemic intensity monitoring, from the earliest stages of the pandemic outbreak, constitutes a critical scientific challenge with major societal stakes. The task is significantly complicated by the low quality of reported infection counts, stemming from emergency and crisis contexts, and by the need for regular (daily) updates, while the pandemic is still active. The present work first proposes a parametric Hidden Markov Model (HMM) aiming to account jointly for epidemic propagation mechanisms and for low-quality data, while imposing epidemiccompliant constraints on the time-varying reproduction number, considered as a proxy for pandemic intensity quantification. Second, and to avoid the arbitrary or expert-based tuning of the parameters of the HMM, data-driven automated selection procedures are devised relying on tailoring a stochastic Expectation Maximization algorithm. Credibility interval-based estimation of the time-varying reproduction number, modeled as a hidden variable, is then obtained from Monte Carlo sampling. The potential of the tools devised here is illustrated on real Covid19 daily new infection counts from Johns Hopkins University repository.

关键词： Statistical modelization Latent variable models Statistical inference Stochastic Expectation-Maximization Covid19 pandemic Reproduction number.

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Kalman Filter for Dynamic Imaging Based on Complex Empirical Covariances

Kalman Filter for Dynamic Imaging Based on Complex Empirical...

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ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Nawel Arab Cyril Cano Isabelle Vin Mohammed Nabil El Korso Eric Chaumette Pascal Larzabal SATIE ENS Paris-Saclay Université Paris-Saclay Gif-sur-Y vette France ISAE-SUPAERO Université de Toulouse Toulouse France L2S CentraleSupelec Université Paris-Saclay Gif-sur-Y vette France

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Pandemic Intensity Estimation from Stochastic Approximation-Based Algorithms

Pandemic Intensity Estimation from Stochastic Approximation-...

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ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Patrice Abry Juliette Chevallier Gersende Fort Barbara Pascal Laboratoire de Physique CNRS ENS Lyon FR IMT UMR 5219 INSA Toulouse Université de Toulouse FR IMT UMR 5219 CNRS Université de Toulouse FR Nantes Université ECN CNRS LS2N FR

Pandemic intensity monitoring, from the earliest stages of the pandemic outbreak, constitutes a critical scientific challenge with major societal stakes. The task is significantly complicated by the low quality of reported infection counts, stemming from emergency and crisis contexts, and by the need for regular (daily) updates, while the pandemic is still active. The present work first proposes a parametric Hidden Markov Model (HMM) aiming to account jointly for epidemic propagation mechanisms and for low-quality data, while imposing epidemic-compliant constraints on the time-varying reproduction number, considered as a proxy for pandemic intensity quantification. Second, and to avoid the arbitrary or expert-based tuning of the parameters of the HMM, data-driven automated selection procedures are devised relying on tailoring a stochastic Expectation-Maximization algorithm. Credibility interval-based estimation of the time-varying reproduction number, modeled as a hidden variable, is then obtained from Monte Carlo sampling. The potential of the tools devised here is illustrated on real Covid19 daily new infection counts from Johns Hopkins University repository.

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RIShield: Enabling Electromagnetic Blackout in Radiation-Sensitive Environments

RIShield: Enabling Electromagnetic Blackout in Radiation-Sen...

引用

ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： G. Encinas-Lago M. Rossanese V. Sciancalepore Marco Di Renzo Xavier Costa-Pérez NEC Laboratories Europe GmbH Heidelberg Germany Université Paris-Saclay CNRS Centrale Supélec Gif-sur-Yvette France i2CAT Foundation and ICREA Barcelona Spain

Reconfigurable Intelligent Surfaces (RIS) have emerged as a disruptive technology with the potential to rev-olutionize wireless communication systems. In this paper, we present RIShield, a novel application of RIS technology specifically designed for radiation-sensitive environments. The aim of RIShield is to enable electromagnetic blackouts, preventing radiation leakage from target areas. We propose a comprehensive framework for RIShield deployment, considering the unique challenges and requirements of radiation-sensitive environments. By strategically positioning RIS panels, we create an intelligent shielding mechanism that selectively absorbs and reflects elec-tromaznetic waves, effectively blocking radiation transmission. To achieve optimal performance, we model the corresponding channel and design a dynamic control that adjusts the RIS con-figuration based on realtime radiation monitoring. By leveraging the principles of reconfiguration and intelligent control, RIShield ensures adaptive and efficient protection while minimizing signal degradation. Through full-wave and ray-tracing simulations, we demonstrate the effectiveness of RIShield in achieving significant electromagnetic attenuation. Our results highlight the potential of RIS technology to address critical concerns in radiation-sensitive environments, paving the way for safer and more secure operations in industries such as healthcare, nuclear facilities, and defense.

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Maximization of the Fisher Information in PDA 8

Maximization of the Fisher Information in PDA

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8th ieee international workshop on computational advances in multi-sensor adaptive processing (CAMSAP)

作者： Payan, Jeremy Jauffret, Claude Perez, Annie-Claude Aix Marseille Univ Univ Toulon CNRS IM2NP Marseille France CS 60584 F-83041 Toulon 9 France

ISBN: (纸本)9781728155494

In a cluttered environment, the probabilistic data association (PDA) model allows constructing efficient estimators. In this case, the Fisher information matrix (FIM) is equal to the FIM in the clean environment multiplied by the so-called information reduction factor. This factor depends implicitly on the detection and false alarms probabilities, hence on the threshold prior to the estimation step. The topic of this paper is to seek the optimal threshold, the one that maximizes the information reduction factor. Whereas the Poisson law is used as an approximation in PDA model, here we consider the binomial law for the large false alarms probabilities. An example, coming from signal processing, illustrates our analysis.

关键词： Fisher information matrix

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