0000000000867505

AUTHOR

Geert Leus

showing 2 related works from this author

Non-cooperative Aerial Base Station Placement via Stochastic Optimization

2019

Autonomous unmanned aerial vehicles (UAVs) with on-board base station equipment can potentially provide connectivity in areas where the terrestrial infrastructure is overloaded, damaged, or absent. Use cases comprise emergency response, wildfire suppression, surveillance, and cellular communications in crowded events to name a few. A central problem to enable this technology is to place such aerial base stations (AirBSs) in locations that approximately optimize the relevant communication metrics. To alleviate the limitations of existing algorithms, which require intensive and reliable communications among AirBSs or between the AirBSs and a central controller, this paper leverages stochastic…

Signal Processing (eess.SP)Computer scienceQuality of serviceDistributed computing05 social sciences050801 communication & media studies020206 networking & telecommunications02 engineering and technologyNetwork utilityCellular communicationBase station0508 media and communicationsControl theoryOptimization and Control (math.OC)0202 electrical engineering electronic engineering information engineeringFOS: Electrical engineering electronic engineering information engineeringFOS: MathematicsStochastic optimizationUse caseElectrical Engineering and Systems Science - Signal ProcessingGradient descentMathematics - Optimization and Control
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Cooperative compressive power spectrum estimation in wireless fading channels

2017

This paper considers multiple wireless sensors that cooperatively estimate the power spectrum of the signals received from several sources. We extend our previous work on cooperative compressive power spectrum estimation to accommodate the scenario where the statistics of the fading channels experienced by different sensors are different. The signals received from the sources are assumed to be time-domain wide-sense stationary processes. Multiple sensors are organized into several groups, where each group estimates a different subset of lags of the temporal correlation. A fusion centre (FC) combines these estimates to obtain the power spectrum. As each sensor group computes correlation esti…

Computer sciencebusiness.industrycorrelation lagSub-Nyquist samplingEstimatorSpectral densityfading020206 networking & telecommunicationsmulticoset sampling02 engineering and technologypower spectrumSignalwide-sense stationarycooperative estimationComputer Science::Networking and Internet Architecture0202 electrical engineering electronic engineering information engineeringWireless020201 artificial intelligence & image processingFadingUniquenessNyquist ratebusinessAlgorithmWireless sensor network2017 International Conference on Electrical Engineering and Informatics (ICELTICs)
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