scholarly journals Compressing Large-Scale Wave Propagation Models via Phase-Preconditioned Rational Krylov Subspaces

2018 ◽  
Vol 16 (4) ◽  
pp. 1486-1518 ◽  
Author(s):  
Vladimir Druskin ◽  
Rob F. Remis ◽  
Mikhail Zaslavsky ◽  
Jörn T. Zimmerling
Keyword(s):  
Wave Propagation ◽  
Large Scale ◽  
Krylov Subspaces ◽  
Propagation Models ◽  
Rational Krylov Subspaces

scholarly journals Identification of Black-Box Wave Propagation Models Using Large-Scale Convex Optimization

2012 ◽  
Vol 45 (16) ◽  
pp. 338-343
Author(s):  
Toon van Waterschoot ◽  
Moritz Diehl ◽  
Marc Moonen ◽  
Geert Leus
Keyword(s):  
Wave Propagation ◽  
Convex Optimization ◽  
Large Scale ◽  
Black Box ◽  
Propagation Models

Solution of Large Scale Evolutionary Problems Using Rational Krylov Subspaces with Optimized Shifts

2009 ◽  
Vol 31 (5) ◽  
pp. 3760-3780 ◽  
Author(s):  
Vladimir Druskin ◽  
Leonid Knizhnerman ◽  
Mikhail Zaslavsky
Keyword(s):  
Large Scale ◽  
Krylov Subspaces ◽  
Rational Krylov Subspaces

scholarly journals Investigation of Empirical Wave Propagation Models in Precision Agriculture

2018 ◽  
Vol 150 ◽  
pp. 06020 ◽  
Author(s):  
N. Sabri ◽  
Mohammed S. S ◽  
Sarah Fouad ◽  
Syed A. A ◽  
Fahad Taha AL-Dhief ◽  
...  
Keyword(s):  
Wave Propagation ◽  
Precision Agriculture ◽  
Large Scale ◽  
Communication Channel ◽  
Path Loss ◽  
Separation Distance ◽  
Propagation Model ◽  
Propagation Models ◽  
Successful Communication ◽  
Vegetation Models

Wireless Sensor Networks have highly proved its contribution in precision agriculture. Communication channel modelling investigation is a highly demanded to achieve a successful communication system where a good wave propagation model is crucially needed. Precision agriculture degrades the traveling waves in various forms in addition to the effects of the large-scale path losses models. This paper reviews the most known theoretical large-scale path losses models such as free space (FSPL) and Plane earth (PE) models as well as the vegetation models represented by Weissberger, ITU-R, FITU-R and COS235 models. Indeed, this work illustrates the effects of many factors on the total path losses such as separation distance between transceivers, antenna heights and the depth of vegetation that presence in the path propagation. In conclusion, the total path loss is computed based on large-scale path losses and the vegetation losses in protected vegetation environment.

Imaging the Chicxulub Central Crater Zone from Large-Scale Seismic Acoustic Wave Propagation and Gravity Modeling

2021 ◽  
Author(s):  
Carlos Ortiz-Aleman ◽  
Ronald Martin ◽  
Jaime Urrutia-Fucugauchi ◽  
Mauricio Orozco del Castillo ◽  
Mauricio Nava-Flores
Keyword(s):  
Wave Propagation ◽  
Acoustic Wave ◽  
Large Scale ◽  
Gravity Modeling ◽  
Acoustic Wave Propagation ◽  
Central Crater

Fast Large-Scale Algorithm for Electromagnetic Wave Propagation in 3D Media

2019 ◽  
Author(s):  
Mitchell Tong Harris ◽  
M. Harper Langston ◽  
Pierre-David Letourneau ◽  
George Papanicolaou ◽  
James Ezick ◽  
...  
Keyword(s):  
Wave Propagation ◽  
Electromagnetic Wave ◽  
Large Scale ◽  
Electromagnetic Wave Propagation

scholarly journals Opportunistic Large Array Propagation Models: A Comprehensive Survey

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4206
Author(s):  
Farhan Nawaz ◽  
Hemant Kumar ◽  
Syed Ali Hassan ◽  
Haejoon Jung
Keyword(s):  
Energy Efficient ◽  
Large Scale ◽  
Performance Metrics ◽  
Experimental Studies ◽  
Cooperative Transmission ◽  
Analytical Models ◽  
Future Research ◽  
Large Array ◽  
Propagation Models ◽  
Comprehensive Survey

Enabled by the fifth-generation (5G) and beyond 5G communications, large-scale deployments of Internet-of-Things (IoT) networks are expected in various application fields to handle massive machine-type communication (mMTC) services. Device-to-device (D2D) communications can be an effective solution in massive IoT networks to overcome the inherent hardware limitations of small devices. In such D2D scenarios, given that a receiver can benefit from the signal-to-noise-ratio (SNR) advantage through diversity and array gains, cooperative transmission (CT) can be employed, so that multiple IoT nodes can create a virtual antenna array. In particular, Opportunistic Large Array (OLA), which is one type of CT technique, is known to provide fast, energy-efficient, and reliable broadcasting and unicasting without prior coordination, which can be exploited in future mMTC applications. However, OLA-based protocol design and operation are subject to network models to characterize the propagation behavior and evaluate the performance. Further, it has been shown through some experimental studies that the most widely-used model in prior studies on OLA is not accurate for networks with networks with low node density. Therefore, stochastic models using quasi-stationary Markov chain are introduced, which are more complex but more exact to estimate the key performance metrics of the OLA transmissions in practice. Considering the fact that such propagation models should be selected carefully depending on system parameters such as network topology and channel environments, we provide a comprehensive survey on the analytical models and framework of the OLA propagation in the literature, which is not available in the existing survey papers on OLA protocols. In addition, we introduce energy-efficient OLA techniques, which are of paramount importance in energy-limited IoT networks. Furthermore, we discuss future research directions to combine OLA with emerging technologies.

scholarly journals Model reduction methods based on Krylov subspaces

Acta Numerica ◽  
2003 ◽  
Vol 12 ◽  
pp. 267-319 ◽  
Author(s):  
Roland W. Freund
Keyword(s):  
Large Scale ◽  
Krylov Subspace ◽  
Circuit Simulation ◽  
Krylov Subspaces ◽  
Lanczos Algorithm ◽  
Linear Dynamical Systems ◽  
Reduced Order ◽  
Reduced Order Modelling ◽  
Reduction Methods ◽  
Modelling Techniques

In recent years, reduced-order modelling techniques based on Krylov-subspace iterations, especially the Lanczos algorithm and the Arnoldi process, have become popular tools for tackling the large-scale time-invariant linear dynamical systems that arise in the simulation of electronic circuits. This paper reviews the main ideas of reduced-order modelling techniques based on Krylov subspaces and describes some applications of reduced-order modelling in circuit simulation.

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