Search results for "FOS: Electrical engineering"

showing 10 items of 127 documents

Performance Analysis of Cooperative V2V and V2I Communications Under Correlated Fading

2019

Cooperative vehicular networks will play a vital role in the coming years to implement various intelligent transportation-related applications. Both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications will be needed to reliably disseminate information in a vehicular network. In this regard, a roadside unit (RSU) equipped with multiple antennas can improve the network capacity. While the traditional approaches assume antennas to experience independent fading, we consider a more practical uplink scenario where antennas at the RSU experience correlated fading. In particular, we evaluate the packet error probability for two renowned antenna correlation models, i.e., cons…

Signal Processing (eess.SP)FOS: Computer and information sciencesvehicle-to-infrastructure (V2I)Computer scienceComputer Science - Information TheoryReliability (computer networking)Real-time computingStackelberg gameComputer Science - Networking and Internet Architecturelangaton tiedonsiirto0502 economics and businessTelecommunications linkFOS: Electrical engineering electronic engineering information engineeringStackelberg competitionpeliteoriaFadingfading channelsElectrical Engineering and Systems Science - Signal ProcessingIntelligent transportation systemerror probabilitygamesNetworking and Internet Architecture (cs.NI)liikennetekniikka050210 logistics & transportationVehicular ad hoc networkreliabilityNetwork packetsignal to noise ratioInformation Theory (cs.IT)Mechanical Engineering05 social sciencesvehicle-to-vehicle (V2V)rakenteettomat verkotTransmitter power outputComputer Science Applicationsantenna correlationAutomotive Engineeringälytekniikkavehicular ad hoc networksantennas
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Nonlinear analysis of charge-pump phase-locked loop: the hold-in and pull-in ranges

2020

In this paper a fairly complete mathematical model of CP-PLL, which reliable enough to serve as a tool for credible analysis of dynamical properties of these circuits, is studied. We refine relevant mathematical definitions of the hold-in and pull-in ranges related to the local and global stability. Stability analysis of the steady state for the charge-pump phase locked loop is non-trivial: straight-forward linearization of available CP-PLL models may lead to incorrect conclusions, because the system is not smooth near the steady state and may experience overload. In this work necessary details for local stability analysis are presented and the hold-in range is computed. An upper estimate o…

Signal Processing (eess.SP)FOS: Electrical engineering electronic engineering information engineeringElectrical Engineering and Systems Science - Signal Processing
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Fast Decentralized Linear Functions Over Edge Fluctuating Graphs

2020

Implementing linear transformations is a key task in the decentralized signal processing framework, which performs learning tasks on data sets distributed over multi-node networks. That kind of network can be represented by a graph. Recently, some decentralized methods have been proposed to compute linear transformations by leveraging the notion of graph shift operator, which captures the local structure of the graph. However, existing approaches have some drawbacks such as considering some special instances of linear transformations, or reducing the family of transformations by assuming that a shift matrix is given such that a subset of its eigenvectors spans the subspace of interest. In c…

Signal Processing (eess.SP)FOS: Electrical engineering electronic engineering information engineeringElectrical Engineering and Systems Science - Signal Processing
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Charge pump phase-locked loop with phase-frequency detector: closed form mathematical model

2019

Charge pump phase-locked loop with phase-frequency detector (CP-PLL) is an electrical circuit, widely used in digital systems for frequency synthesis and synchronization of the clock signals. In this paper a non-linear second-order model of CP-PLL is rigorously derived. The obtained model obviates the shortcomings of previously known second-order models of CP-PLL. Pull-in time is estimated for the obtained second-order CP-PLL.

Signal Processing (eess.SP)FOS: Electrical engineering electronic engineering information engineeringElectrical Engineering and Systems Science - Signal Processing
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Designing Asymmetric Shift Operators for Decentralized Subspace Projection

2020

A large number of applications in wireless sensor networks include projecting a vector of noisy observations onto a subspace dictated by prior information about the field being monitored. In general, accomplishing such a task in a centralized fashion, entails a large power consumption, congestion at certain nodes, and suffers from robustness issues against possible node failures. Computing such projections in a decentralized fashion is an alternative solution that solves these issues. Recent works have shown that this task can be done via the so-called graph filters where only local inter-node communication is performed in a distributed manner using a graph shift operator. Existing methods …

Signal Processing (eess.SP)FOS: Electrical engineering electronic engineering information engineeringElectrical Engineering and Systems Science - Signal Processing
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Interpolation and Gap Filling of Landsat Reflectance Time Series

2018

Products derived from a single multispectral sensor are hampered by a limited spatial, spectral or temporal resolutions. Image fusion in general and downscaling/blending in particular allow to combine different multiresolution datasets. We present here an optimal interpolation approach to generate smoothed and gap-free time series of Landsat reflectance data. We fuse MODIS (moderate-resolution imaging spectroradiometer) and Landsat data globally using the Google Earth Engine (GEE) platform. The optimal interpolator exploits GEE ability to ingest large amounts of data (Landsat climatologies) and uses simple linear operations that scale easily in the cloud. The approach shows very good result…

Signal Processing (eess.SP)Image fusion010504 meteorology & atmospheric sciencesComputer scienceMultispectral image0211 other engineering and technologies02 engineering and technology01 natural sciencesReflectivitySpectroradiometerFOS: Electrical engineering electronic engineering information engineeringTime seriesElectrical Engineering and Systems Science - Signal ProcessingScale (map)Image resolution021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingInterpolationDownscaling
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Online Non-linear Topology Identification from Graph-connected Time Series

2021

Estimating the unknown causal dependencies among graph-connected time series plays an important role in many applications, such as sensor network analysis, signal processing over cyber-physical systems, and finance engineering. Inference of such causal dependencies, often know as topology identification, is not well studied for non-linear non-stationary systems, and most of the existing methods are batch-based which are not capable of handling streaming sensor signals. In this paper, we propose an online kernel-based algorithm for topology estimation of non-linear vector autoregressive time series by solving a sparse online optimization framework using the composite objective mirror descent…

Signal Processing (eess.SP)Kernel (linear algebra)Signal processingSeries (mathematics)Autoregressive modelComputer scienceFOS: Electrical engineering electronic engineering information engineeringGraph (abstract data type)InferenceTopology (electrical circuits)Electrical Engineering and Systems Science - Signal ProcessingWireless sensor networkAlgorithm
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Network-Assisted Resource Allocation with Quality and Conflict Constraints for V2V Communications

2018

The 3rd Generation Partnership Project (3GPP) has recently established in Rel. 14 a network-assisted resource allocation scheme for vehicular broadcast communications. Such novel paradigm is known as vehicle--to--vehicle (V2V) \textit{mode-3} and consists in eNodeBs engaging only in the distribution of sidelink subchannels among vehicles in coverage. Thereupon, without further intervention of the former, vehicles will broadcast their respective signals directly to their counterparts. Because the allotment of subchannels takes place intermittently to reduce signaling, it must primarily be conflict-free in order not to jeopardize the reception of signals. We have identified four pivotal types…

Signal Processing (eess.SP)Linear programmingComputer scienceReliability (computer networking)media_common.quotation_subject050801 communication & media studies02 engineering and technology0508 media and communications0202 electrical engineering electronic engineering information engineeringFOS: Electrical engineering electronic engineering information engineeringResource managementQuality (business)Electrical Engineering and Systems Science - Signal Processingmedia_commonbusiness.industryQuality of service05 social sciences020206 networking & telecommunicationsMaximizationKnapsack problemquality of serviceResource allocationbroadcast vehicular communicationssubchannel allocationbusinessComputer network
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Data-Driven Spectrum Cartography via Deep Completion Autoencoders

2019

Spectrum maps, which provide RF spectrum metrics such as power spectral density for every location in a geographic area, find numerous applications in wireless communications such as interference control, spectrum management, resource allocation, and network planning to name a few. Spectrum cartography techniques construct these maps from a collection of measurements collected by spatially distributed sensors. Due to the nature of the propagation of electromagnetic waves, spectrum maps are complicated functions of the spatial coordinates. For this reason, model-free approaches have been preferred. However, all existing schemes rely on some interpolation algorithm unable to learn from data. …

Signal Processing (eess.SP)Network architectureComputer sciencebusiness.industry05 social sciencesSpectral density050801 communication & media studiesSpectrum managementNetwork planning and design0508 media and communicationsSpatial reference system0502 economics and businessFOS: Electrical engineering electronic engineering information engineeringResource allocationWireless050211 marketingElectrical Engineering and Systems Science - Signal ProcessingbusinessVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550CartographyInterpolation
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Accurate Graph Filtering in Wireless Sensor Networks

2020

Wireless sensor networks (WSNs) are considered as a major technology enabling the Internet of Things (IoT) paradigm. The recent emerging Graph Signal Processing field can also contribute to enabling the IoT by providing key tools, such as graph filters, for processing the data associated with the sensor devices. Graph filters can be performed over WSNs in a distributed manner by means of a certain number of communication exchanges among the nodes. But, WSNs are often affected by interferences and noise, which leads to view these networks as directed, random and time-varying graph topologies. Most of existing works neglect this problem by considering an unrealistic assumption that claims the…

Signal Processing (eess.SP)Networking and Internet Architecture (cs.NI)FOS: Computer and information sciencesComputer Networks and CommunicationsComputer scienceNetwork packetDistributed computing020206 networking & telecommunications02 engineering and technologyNetwork topologyGraphComputer Science ApplicationsComputer Science - Networking and Internet ArchitectureHardware and ArchitectureSignal Processing0202 electrical engineering electronic engineering information engineeringComputer Science::Networking and Internet ArchitectureFOS: Electrical engineering electronic engineering information engineeringGraph (abstract data type)020201 artificial intelligence & image processingElectrical Engineering and Systems Science - Signal ProcessingWireless sensor networkInformation Systems
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