Energy Consumption Minimization for UAV-Assisted Network in Hotspot Area
Unmanned aerial vehicles (UAVs) play a crucial role in enhancing network coverage and capacity, especially in areas with high user density or limited infrastructure. This paper proposes an effective UAV-assisted offloading framework to minimize the energy consumption of both users and UAVs in an air...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-02-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/9/3/178 |
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| author | Jinxi Zhang Saidiwaerdi Maimaiti Weidong Gao Kaisa Zhang |
| author_facet | Jinxi Zhang Saidiwaerdi Maimaiti Weidong Gao Kaisa Zhang |
| author_sort | Jinxi Zhang |
| collection | DOAJ |
| description | Unmanned aerial vehicles (UAVs) play a crucial role in enhancing network coverage and capacity, especially in areas with high user density or limited infrastructure. This paper proposes an effective UAV-assisted offloading framework to minimize the energy consumption of both users and UAVs in an air-to-ground (A2G) network. First, UAVs are deployed by jointly considering the user distribution and guaranteeing the quality of service (QoS) of users. Further, user association, power control, and bandwidth allocation are jointly optimized, aiming to minimize the power consumption of users. Considering user mobility, the positions of UAVs are continuously refined using the double deep Q-network (DDQN) algorithm to reduce the weighted energy consumption of users and UAVs. Simulation results show that the proposed algorithm has better performance in reducing the total energy consumption compared with benchmark schemes. |
| format | Article |
| id | doaj-art-c1ada195c2d84e45aee15ad4bcfe7ac2 |
| institution | OA Journals |
| issn | 2504-446X |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-c1ada195c2d84e45aee15ad4bcfe7ac22025-08-20T02:11:22ZengMDPI AGDrones2504-446X2025-02-019317810.3390/drones9030178Energy Consumption Minimization for UAV-Assisted Network in Hotspot AreaJinxi Zhang0Saidiwaerdi Maimaiti1Weidong Gao2Kaisa Zhang3Institute of Artificial Intelligence in Sports, Capital University of Physical Education and Sports, Beijing 100191, ChinaSchool of Information Engineering, Xinjiang Institute of Engineering, Urumqi 830023, ChinaDepartment of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100083, ChinaDepartment of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100083, ChinaUnmanned aerial vehicles (UAVs) play a crucial role in enhancing network coverage and capacity, especially in areas with high user density or limited infrastructure. This paper proposes an effective UAV-assisted offloading framework to minimize the energy consumption of both users and UAVs in an air-to-ground (A2G) network. First, UAVs are deployed by jointly considering the user distribution and guaranteeing the quality of service (QoS) of users. Further, user association, power control, and bandwidth allocation are jointly optimized, aiming to minimize the power consumption of users. Considering user mobility, the positions of UAVs are continuously refined using the double deep Q-network (DDQN) algorithm to reduce the weighted energy consumption of users and UAVs. Simulation results show that the proposed algorithm has better performance in reducing the total energy consumption compared with benchmark schemes.https://www.mdpi.com/2504-446X/9/3/178unmanned aerial vehicle (UAV) deploymentpower controlresource allocationdouble deep Q-network (DDQN) |
| spellingShingle | Jinxi Zhang Saidiwaerdi Maimaiti Weidong Gao Kaisa Zhang Energy Consumption Minimization for UAV-Assisted Network in Hotspot Area Drones unmanned aerial vehicle (UAV) deployment power control resource allocation double deep Q-network (DDQN) |
| title | Energy Consumption Minimization for UAV-Assisted Network in Hotspot Area |
| title_full | Energy Consumption Minimization for UAV-Assisted Network in Hotspot Area |
| title_fullStr | Energy Consumption Minimization for UAV-Assisted Network in Hotspot Area |
| title_full_unstemmed | Energy Consumption Minimization for UAV-Assisted Network in Hotspot Area |
| title_short | Energy Consumption Minimization for UAV-Assisted Network in Hotspot Area |
| title_sort | energy consumption minimization for uav assisted network in hotspot area |
| topic | unmanned aerial vehicle (UAV) deployment power control resource allocation double deep Q-network (DDQN) |
| url | https://www.mdpi.com/2504-446X/9/3/178 |
| work_keys_str_mv | AT jinxizhang energyconsumptionminimizationforuavassistednetworkinhotspotarea AT saidiwaerdimaimaiti energyconsumptionminimizationforuavassistednetworkinhotspotarea AT weidonggao energyconsumptionminimizationforuavassistednetworkinhotspotarea AT kaisazhang energyconsumptionminimizationforuavassistednetworkinhotspotarea |