Joint Optimization Algorithm for UAV-Assisted Caching and Charging Based on Wireless Energy Harvesting
The proliferation of mobile terminal applications and the increasing energy consumption of chips have raised concerns about insufficient power in mobile user terminals. In response to this issue, this paper proposes a joint optimization algorithm for UAV-assisted caching and charging based on non-or...
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MDPI AG
2025-04-01
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| author | Yumeng Zhu Qi Zhu |
| author_facet | Yumeng Zhu Qi Zhu |
| author_sort | Yumeng Zhu |
| collection | DOAJ |
| description | The proliferation of mobile terminal applications and the increasing energy consumption of chips have raised concerns about insufficient power in mobile user terminals. In response to this issue, this paper proposes a joint optimization algorithm for UAV-assisted caching and charging based on non-orthogonal multiple access (NOMA) within the context of mobile edge caching scenarios. The proposed algorithm considers the revenue generated from UAVs providing caching and charging services to users, as well as the cost associated with leasing cache files and the UAV energy consumption. The optimization problem aimed at maximizing UAV utility is established under constraints related to power and cache capacity. To address this mixed-integer programming problem, we divided it into two parts. The first part uses the Stackelberg–Bertrand game to optimize file pricing and the UAV cache strategy. In the second part, the block coordinate descent (BCD) method is used to optimize the UAV transmission power distribution, positioning, and user pairing. The joint optimization problem is divided into three subproblems, which use the Lagrange multiplier method, a simulated annealing algorithm, and a particle swarm optimization algorithm. Simulation results demonstrate that the proposed algorithm effectively reduces user transmission delay while also improving overall revenue generated by UAVs. |
| format | Article |
| id | doaj-art-453800a3a7f24b888dc090dd0909ca7e |
| institution | DOAJ |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-453800a3a7f24b888dc090dd0909ca7e2025-08-20T03:08:44ZengMDPI AGApplied Sciences2076-34172025-04-01157390810.3390/app15073908Joint Optimization Algorithm for UAV-Assisted Caching and Charging Based on Wireless Energy HarvestingYumeng Zhu0Qi Zhu1Jiangsu Key Laboratory of Wireless Communications, Nanjing University of Posts and Telecommunications, Nanjing 210003, ChinaJiangsu Key Laboratory of Wireless Communications, Nanjing University of Posts and Telecommunications, Nanjing 210003, ChinaThe proliferation of mobile terminal applications and the increasing energy consumption of chips have raised concerns about insufficient power in mobile user terminals. In response to this issue, this paper proposes a joint optimization algorithm for UAV-assisted caching and charging based on non-orthogonal multiple access (NOMA) within the context of mobile edge caching scenarios. The proposed algorithm considers the revenue generated from UAVs providing caching and charging services to users, as well as the cost associated with leasing cache files and the UAV energy consumption. The optimization problem aimed at maximizing UAV utility is established under constraints related to power and cache capacity. To address this mixed-integer programming problem, we divided it into two parts. The first part uses the Stackelberg–Bertrand game to optimize file pricing and the UAV cache strategy. In the second part, the block coordinate descent (BCD) method is used to optimize the UAV transmission power distribution, positioning, and user pairing. The joint optimization problem is divided into three subproblems, which use the Lagrange multiplier method, a simulated annealing algorithm, and a particle swarm optimization algorithm. Simulation results demonstrate that the proposed algorithm effectively reduces user transmission delay while also improving overall revenue generated by UAVs.https://www.mdpi.com/2076-3417/15/7/3908unmanned aerial vehiclemobile edge cachingwireless energy harvestingnon-orthogonal multiple accessStackelberg game |
| spellingShingle | Yumeng Zhu Qi Zhu Joint Optimization Algorithm for UAV-Assisted Caching and Charging Based on Wireless Energy Harvesting Applied Sciences unmanned aerial vehicle mobile edge caching wireless energy harvesting non-orthogonal multiple access Stackelberg game |
| title | Joint Optimization Algorithm for UAV-Assisted Caching and Charging Based on Wireless Energy Harvesting |
| title_full | Joint Optimization Algorithm for UAV-Assisted Caching and Charging Based on Wireless Energy Harvesting |
| title_fullStr | Joint Optimization Algorithm for UAV-Assisted Caching and Charging Based on Wireless Energy Harvesting |
| title_full_unstemmed | Joint Optimization Algorithm for UAV-Assisted Caching and Charging Based on Wireless Energy Harvesting |
| title_short | Joint Optimization Algorithm for UAV-Assisted Caching and Charging Based on Wireless Energy Harvesting |
| title_sort | joint optimization algorithm for uav assisted caching and charging based on wireless energy harvesting |
| topic | unmanned aerial vehicle mobile edge caching wireless energy harvesting non-orthogonal multiple access Stackelberg game |
| url | https://www.mdpi.com/2076-3417/15/7/3908 |
| work_keys_str_mv | AT yumengzhu jointoptimizationalgorithmforuavassistedcachingandchargingbasedonwirelessenergyharvesting AT qizhu jointoptimizationalgorithmforuavassistedcachingandchargingbasedonwirelessenergyharvesting |