Analysis, estimation and prediction of fading for a time-variant UAV-ground control station wireless channel for cognitive communications

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dc.contributor.authorBelal, Rafi
dc.contributor.examiningcommitteeMojabi, Puyan (Electrical and Computer Engineering) Sepehri, Nariman (Mechanical Engineering) Prentice, Barry (Supply Chain Management)en_US
dc.contributor.supervisorKinsner, Witold (Electrical and Computer Engineering)en_US
dc.date.accessioned2016-01-15T15:10:15Z
dc.date.available2016-01-15T15:10:15Z
dc.date.issued2015
dc.degree.disciplineElectrical and Computer Engineeringen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractThis thesis presents a design and implementation of a long-range communication subsystem for a UAV and a ground control station. The subsystem is a low-cost alternative employing a line of sight, local communication network for optimal communications between a low-altitude UAV and a portable ground control station. In this thesis, real world experiments are conducted to model the time-variant wireless channel between a low-altitude micro-UAV and a portable ground control station operating in an urban environment. The large-scale and small-scale fading coefficients are calculated and analyzed for this dynamic channel. The channel properties, along with the fading distribution parameters, are computed and analyzed for two most popular antenna configurations for UAV systems (Yagi to omnidirectional and omnidirectional to omnidirectional). For the Yagi-to-omnidirectional link, the effects of three major impacting factors i.e. propagation distance, antenna gains in specific spherical angles and polarization mismatch factor on the overall fading distribution is investigated. Through regression analysis, a multiple-regression model is derived that estimates the instantaneous fading parameter, given these channel conditions. For this model, a modified particle-swarm optimization algorithm is designed and implemented to estimate the underlying model coefficients, given the instantaneous fading information. The implementation of this algorithm, along with the regression model, demonstrates that a sufficient approximation of the fading parameter can be provided for any given wireless channel when the impacting factors and instantaneous fading information is available.en_US
dc.description.noteFebruary 2016en_US
dc.identifier.urihttp://hdl.handle.net/1993/31089
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectUAVen_US
dc.subjectGround control stationen_US
dc.subjectFadingen_US
dc.subjectTime-variant channelen_US
dc.subjectWireless channelen_US
dc.subjectCognitive communicationsen_US
dc.titleAnalysis, estimation and prediction of fading for a time-variant UAV-ground control station wireless channel for cognitive communicationsen_US
dc.typemaster thesisen_US
local.subject.manitobayesen_US
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