Energy-Efficient Data Uploading for Cellular-Connected UAV Systems
Integrating unmanned aerial vehicles (UAVs) into cellular networks offers a promising solution to support their efficient operations and achieve high-quality communication with the ground. In this paper, we consider a cellular-connected UAV communication system, in which one energy-constrained UAV f...
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| Published in: | IEEE transactions on wireless communications Vol. 19; no. 11; pp. 7279 - 7292 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
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New York
IEEE
01.11.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1536-1276, 1558-2248 |
| Online Access: | Get full text |
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| Abstract | Integrating unmanned aerial vehicles (UAVs) into cellular networks offers a promising solution to support their efficient operations and achieve high-quality communication with the ground. In this paper, we consider a cellular-connected UAV communication system, in which one energy-constrained UAV flies from a given initial location to a final location while uploading data to the ground base stations (GBSs) along its flight. We study the joint design of UAV operation time, communication scheduling, as well as UAV trajectory and transmit power to maximize the data uploading throughput, subject to the communication quality of service (QoS) requirement and UAV energy budget constraints. We first consider an offline design approach by utilizing only the channel distribution information (CDI) that is available prior to the UAV's flight, which is formulated as a non-convex optimization problem and challenging to solve. By using path disretization and successive convex approximation (SCA) techniques, an efficient alternating optimization algorithm is proposed, which can converge to a solution that satisfies the Karush-Kuhn-Tucker (KKT) conditions. Then, we further study the online design approach by utilizing the instantaneous channel state information (CSI) that is available to the UAV in real time along its flight. As the online design problem has similar structure as that of the offline design, an adaptive online optimization algorithm is proposed. To further reduce the computational complexity, a low-complexity online algorithm based on receding horizon optimization (RHO) is developed by utilizing a combined offline and online design approach. Simulations are conducted to corroborate our study and the results demonstrate the performance gain of proposed designs as compared to various baseline schemes. Furthermore, our results unveil the tradeoff between system throughput and UAV endurance in the considered system. |
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| AbstractList | Integrating unmanned aerial vehicles (UAVs) into cellular networks offers a promising solution to support their efficient operations and achieve high-quality communication with the ground. In this paper, we consider a cellular-connected UAV communication system, in which one energy-constrained UAV flies from a given initial location to a final location while uploading data to the ground base stations (GBSs) along its flight. We study the joint design of UAV operation time, communication scheduling, as well as UAV trajectory and transmit power to maximize the data uploading throughput, subject to the communication quality of service (QoS) requirement and UAV energy budget constraints. We first consider an offline design approach by utilizing only the channel distribution information (CDI) that is available prior to the UAV’s flight, which is formulated as a non-convex optimization problem and challenging to solve. By using path disretization and successive convex approximation (SCA) techniques, an efficient alternating optimization algorithm is proposed, which can converge to a solution that satisfies the Karush-Kuhn-Tucker (KKT) conditions. Then, we further study the online design approach by utilizing the instantaneous channel state information (CSI) that is available to the UAV in real time along its flight. As the online design problem has similar structure as that of the offline design, an adaptive online optimization algorithm is proposed. To further reduce the computational complexity, a low-complexity online algorithm based on receding horizon optimization (RHO) is developed by utilizing a combined offline and online design approach. Simulations are conducted to corroborate our study and the results demonstrate the performance gain of proposed designs as compared to various baseline schemes. Furthermore, our results unveil the tradeoff between system throughput and UAV endurance in the considered system. |
| Author | Zhan, Cheng Zeng, Yong |
| Author_xml | – sequence: 1 givenname: Cheng orcidid: 0000-0002-0971-6748 surname: Zhan fullname: Zhan, Cheng email: zhanc@swu.edu.cn organization: School of Computer and Information Science, Southwest University, Chongqing, China – sequence: 2 givenname: Yong orcidid: 0000-0002-3670-0434 surname: Zeng fullname: Zeng, Yong email: yong_zeng@seu.edu.cn organization: National Mobile Communications Research Laboratory, Southeast University, Nanjing, China |
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| SubjectTerms | Adaptive algorithms Cellular communication Cellular networks Cellular-connected UAV Communication Communications systems Complexity Computational geometry Constraints Convexity data uploading Design optimization Energy budget energy consumption Ground stations Kuhn-Tucker method Optimization Optimization algorithms Quality of service Throughput Trajectory UAV operation time Unmanned aerial vehicles |
| Title | Energy-Efficient Data Uploading for Cellular-Connected UAV Systems |
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