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dc.contributorDepartment of Electrical and Electronic Engineeringen_US
dc.contributor.advisorZhang, Shuowen (EEE)en_US
dc.creatorShi, Wenjie-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/14050-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic Universityen_US
dc.rightsAll rights reserveden_US
dc.titleTrajectory optimization for cellular-connected UAVen_US
dcterms.abstractIn this paper, we first study the optimal three-dimensional (3D) path planning for a cellular-connected unmanned aerial vehicle (UAV) which is given a mission to fly from given initial to final locations by using minimum time, while guaranteeing a good channel quality in terms of the expected signal-to-noise ratio (SNR) between UAV and its associated ground base stations (GBSs) during the flight. Specifically, we construct a radio map to quantize the UAV's flying area to be many grid points thus reducing the computing complexity. After that we depict the grids achieving the expected SNR goal which is so-called SNR map and derive the optimal trajectory by solving an equivalent shortest path problem (SPP) in graph theory. Then, we focus on the effectiveness of coordinated multi-point (CoMP) transmission technique [1] to enhance the channel quality when UAV associates with GBSs during its mission. To tackle this problem, we construct two SNR maps for UAVs equipped with conventional single antenna (CSA) transmission technique and CoMP technique, respectively. With the SNR constraint gradually increasing, we compare the distance of optimal trajectory by exploiting different transmission techniques. Numerical results show that by leveraging CoMP technique, UAV can fly a shorter distance under the same SNR constraint and even complete mission with a stricter SNR constraint under which UAV with CSA technique fails to complete mission. Finally, we propose an energy consumption strategy to find the minimum energy consumption for the UAV with CoMP technique flying from initial to final location along optimal trajectory. Specifically, we control part of the GBSs off until the SNR is just larger than the expected SNR at each grid, so that these unhelpful GBSs can be turned off and save energy. Numerical results show that the strategy can save a huge part of energy.en_US
dcterms.extent1 volume (unpaged) : color illustrationsen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2023en_US
dcterms.educationalLevelM.Sc.en_US
dcterms.educationalLevelAll Masteren_US
dcterms.accessRightsrestricted accessen_US

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Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/14050