Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Electrical and Electronic Engineering | en_US |
| dc.contributor.advisor | Zhang, Shuowen (EEE) | en_US |
| dc.contributor.advisor | Lau, C. M. Francis (EEE) | en_US |
| dc.creator | Du, Xiangming | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/13758 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Trajectory optimization for cellular-connected UAV in future wireless networks | en_US |
| dcterms.abstract | Cellular-enabled unmanned aerial vehicle (UAV) communication or cellular-connected UAV is a promising approach for realizing high-quality UAV-to-ground communications. In this thesis, we investigate brand new challenges for cellular-connected UAVs, separately focusing on a sensing problem for a target whose exact location is unknown and random and a handover awareness problem for cellular-enabled UAV communication. | en_US |
| dcterms.abstract | Firstly, we study a trajectory optimization of a cellular-connected UAV which bears a mission of sensing the location of a ground target based on its prior location distribution information where the UAV maintains satisfactory communication with ground base stations (GBSs). We focus on a challenging scenario where the exact location of the target to be sensed is unknown and random, while its prior distribution is known and stored in a novel target location distribution map. Based on this map, the probability for the UAV to successfully sense the target can be extracted as a function of the UAV's location. The UAV exploits the target location distribution map to visit specific locations to maximize the sensing probability. We aim to optimize the UAV's trajectory between two pre-determined locations to maximize the total sensing probability during its flight, subject to a GBS-UAV communication quality constraint at each time instant during its flight and a maximum mission completion time constraint. However, this new problem is a constrained longest path problem (CLPP), which is non-convex and NP-Hard. Particularly, the optimal trajectory needs to strike the best balance between the total probability, expected SNR, and maximum flying distance. To address this problem, we propose three high-quality suboptimal solutions, which can achieve significantly improved sensing performance. | en_US |
| dcterms.abstract | Secondly, we study a cellular-connected UAV which aims to complete a mission of flying between two pre-determined locations while maintaining satisfactory communication quality with the GBSs. Due to the potentially long distance of the UAV's flight, frequent handovers may be incurred among different GBSs, which leads to various practical issues such as large delay and synchronization overhead. To this end, we mathematically derive the handover function, which is critically dependent on the UAV's trajectory and GBS-UAV associations. We aim to minimize the number of GBS handovers by jointly optimizing the UAV's flight trajectory and the GBS-UAV association, subject to a communication quality constraint and a maximum mission completion time constraint. Although this problem is non-convex and difficult to solve, we derive useful structures of the optimal solution, based on which we propose an efficient algorithm based on graph theory and Lagrangian relaxation for finding a high-quality suboptimal solution in polynomial time. Numerical results validate the effectiveness of our proposed trajectory design. | en_US |
| dcterms.abstract | In summary, this thesis studies two cellular-connected UAV trajectory optimization problems in future wireless networks, and proposes high-quality solutions to tackle them. For sensing a target without exact location information, the proposed trajectory designs achieve significantly improved sensing performance by leveraging the prior location distribution information of the target, which provides a useful guideline for cellular-connected UAVs to sense targets. Moreover, the investigation of handovers provides a new model for handover analysis, and the designed trajectory significantly decreases the number of handovers, which provides valuable principles for cellular-connected UAVs on their safe flight. | en_US |
| dcterms.extent | 81 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2025 | en_US |
| dcterms.educationalLevel | M.Phil. | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.accessRights | open access | en_US |
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