- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
- Chinese S&T Journal Citation Reports
- Chinese Science Citation Database
| Citation: | CHENG Kaijun, FANG Xuming, XU Wentao. Performance Optimization for Intelligent Reflecting Surface and Wireless Power Transfer-Aided Unmanned Aerial Vehicle Edge Computing Network[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20250286
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To address the issues of degraded communication quality, reduced task offloading performance, and constrained computational efficiency in unmanned aerial vehicle (UAV) edge computing networks caused by poor communication conditions and limited wireless device energy when terrestrial wireless infrastructure fails, supported by intelligent reflecting surface (IRS) and wireless power transfer (WPT) technologies, UAV edge computing networks were studied, and corresponding optimization schemes were proposed. On the one hand, by adopting IRS technology, the communication quality of wireless links was optimized through real-time adjustment of the reflected signal phase to direct signals toward the target, thereby improving the task offloading capability. On the other hand, WPT technology was used to supply temporary energy to wireless devices, providing power support for them to execute computation tasks. Under this network, through an iterative optimization method, the spectrum resources, CPU frequencies and transmitting power of wireless devices, time allocation between WPT and task offloading, IRS coefficients, and UAV flying trajectory were analyzed and derived, and the network’s computation rate was optimized. The simulation results verify that the proposed scheme effectively improves the overall computing performance of the network. In terms of computation rate, the proposed scheme outperforms various UAV flying schemes by at least 34.3%, various task processing mechanisms by at least 15.3%, and different optimization schemes by at least 15.9%. The above results demonstrate that the proposed scheme can significantly improve the edge computing performance in UAV scenarios and can provide an efficient and reliable solution for wireless device energy supply and collaborative computation task processing in UAV edge computing network.
| [1] |
Deng C L, Fang X M, Wang X B. UAV-enabled mobile-edge computing for AI applications: joint model decision, resource allocation, and trajectory optimization[J]. IEEE Internet of Things Journal, 2023, 10(7): 5662-5675. doi: 10.1109/JIOT.2022.3151619
|
| [2] |
Mozaffari M, Saad W, Bennis M, et al. Mobile unmanned aerial vehicles (UAVs) for energy-efficient Internet of Things communications[J]. IEEE Transactions on Wireless Communications, 2017, 16(11): 7574-7589. doi: 10.1109/TWC.2017.2751045
|
| [3] |
Zhao M X, Zhang R Q, He Z L, et al. Joint optimization of trajectory, offloading, caching, and migration for UAV-assisted MEC[J]. IEEE Transactions on Mobile Computing, 2025, 24(3): 1981-1998. doi: 10.1109/TMC.2024.3486995
|
| [4] |
鞠宏浩, 程楷钧, 邓彩连, 等. 无人机空地网络研究综述[J]. 西南交通大学学报, 2024, 59(4): 877-889.
Ju Honghao, Cheng Kaijun, Deng Cailian, et al. A survey on air-ground networks of unmanned aerial vehicles[J]. Journal of Southwest Jiaotong University, 2024, 59(4): 877-889.
|
| [5] |
Li M S, Cheng N, Gao J, et al. Energy-efficient UAV-assisted mobile edge computing: resource allocation and trajectory optimization[J]. IEEE Transactions on Vehicular Technology, 2020, 69(3): 3424-3438. doi: 10.1109/TVT.2020.2968343
|
| [6] |
李校林, 江雨桑. 无人机辅助移动边缘计算中的任务卸载算法[J]. 计算机应用, 2023, 43(6): 1893-1899.
Li Xiaolin, Jiang Yusang. Task offloading algorithm for UAV-assisted mobile edge computing[J]. Journal of Computer Applications, 2023, 43(6): 1893-1899.
|
| [7] |
周晓天, 杨潇辉, 张海霞, 等. 无人机辅助边缘计算网络的任务卸载与资源分配联合优化[J]. 电子与信息学报, 2024, 46(12): 4399-4408.
Zhou Xiaotian, Yang Xiaohui, Zhang Haixia, et al. Joint optimization of task offloading and resource allocation for unmanned aerial vehicle-assisted edge computing network[J]. Journal of Electronics & Information Technology, 2024, 46(12): 4399-4408.
|
| [8] |
Liu C J, Zhong Y L, Wu R L, et al. Deep reinforcement learning based 3D-trajectory design and task offloading in UAV-enabled MEC system[J]. IEEE Transactions on Vehicular Technology, 2025, 74(2): 3185-3195. doi: 10.1109/TVT.2024.3469977
|
| [9] |
Han Z H, Zhou T, Xu T H, et al. Joint user association and deployment optimization for delay-minimized UAV-aided MEC networks[J]. IEEE Wireless Communications Letters, 2023, 12(10): 1791-1795. doi: 10.1109/LWC.2023.3294749
|
| [10] |
Xiang K, He Y J. UAV-assisted MEC system considering UAV trajectory and task offloading strategy[C]//ICC 2023 - IEEE International Conference on Communications. Piscataway: IEEE, 2023: 4677-4682.
|
| [11] |
Qin X T, Song Z Y, Hou T W, et al. Joint optimization of resource allocation, phase shift, and UAV trajectory for energy-efficient RIS-assisted UAV-enabled MEC systems[J]. IEEE Transactions on Green Communications and Networking, 2023, 7(4): 1778-1792. doi: 10.1109/TGCN.2023.3287604
|
| [12] |
Chen Z, Tang J, Wen M W, et al. Reconfigurable intelligent surface assisted MEC offloading in NOMA-enabled IoT networks[J]. IEEE Transactions on Communications, 2023, 71(8): 4896-4908. doi: 10.1109/TCOMM.2023.3277005
|
| [13] |
王梓辰, 聂晋阁, 刘轩, 等. 智能反射表面辅助的无人机数据传输与计算: 综述与展望[J]. 电讯技术, 2026, 66(2): 327-342.
Wang Zichen, Nie Jinge, Liu Xuan, et al. Reconfigurable intelligent surface-assisted UAV data transmission and computation: research review and future prospects[J]. Telecommunication Engineering, 2026, 66(2): 327-342.
|
| [14] |
Khaleghi H, Paquelet S. Adaptive low-overhead channel estimation tracking in RIS-assisted systems[J]. IEEE Access, 2025, 13: 88589-88599. doi: 10.1109/ACCESS.2025.3570772
|
| [15] |
崔亚平, 应兆朋, 何鹏, 等. 空中智能反射面增强的URLLC多无人机网络[J]. 西南交通大学学报, 2024, 59(4): 907-916.
Cui Yaping, Ying Zhaopeng, He Peng, et al. Ultra-reliable low-latency communication multi-unmanned aerial vehicle network assisted by intelligent reflecting surface in air[J]. Journal of Southwest Jiaotong University, 2024, 59(4): 907-916.
|
| [16] |
Wu Q Q, Zhang R. Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming[J]. IEEE Transactions on Wireless Communications, 2019, 18(11): 5394-5409. doi: 10.1109/TWC.2019.2936025
|
| [17] |
Jain T, Bitragunta S, Bhatia A. Adaptive RIS design and optimization for cooperative RIS-assisted wireless systems[J]. IEEE Open Journal of Vehicular Technology, 2025, 6: 2022-2032. doi: 10.1109/OJVT.2025.3588543
|
| [18] |
Chêne T, Bounhar O, Othman G R, et al. Adaptive passive beamforming in RIS-aided communications with Q-learning[C]//2025 IEEE Wireless Communications and Networking Conference (WCNC). Piscataway: IEEE, 2025: 1-6.
|
| [19] |
Chu Z, Xiao P, Shojafar M, et al. Intelligent reflecting surface assisted mobile edge computing for Internet of Things[J]. IEEE Wireless Communications Letters, 2021, 10(3): 619-623. doi: 10.1109/LWC.2020.3040607
|
| [20] |
Cheng K J, Fang X M, Wang X B. Energy efficient edge computing and data compression collaboration scheme for UAV-assisted network[J]. IEEE Transactions on Vehicular Technology, 2023, 72(12): 16395-16408. doi: 10.1109/TVT.2023.3289962
|
| [21] |
Shi L Q, Ye Y H, Chu X L, et al. Energy-efficient resource allocation for backscatter-assisted wireless powered MEC[J]. IEEE Transactions on Vehicular Technology, 2023, 72(7): 9591-9596. doi: 10.1109/TVT.2023.3246237
|
| [22] |
Khan T A, Yazdan A, Heath R W. Optimization of power transfer efficiency and energy efficiency for wireless-powered systems with massive MIMO[J]. IEEE Transactions on Wireless Communications, 2018, 17(11): 7159-7172. doi: 10.1109/TWC.2018.2865727
|
| [23] |
刘建华, 李国华, 刘佳嘉, 等. 无人机辅助无线供电移动边缘计算系统的多目标优化[J]. 电子与信息学报, 2025, 47(10): 3632-3645.
Liu Jianhua, Li Guohua, Liu Jiajia, et al. Multi-objective optimization of UAV-assisted wireless power transfer mobile edge computing system[J]. Journal of Electronics & Information Technology, 2025, 47(10): 3632-3645.
|
| [24] |
陈训杨, 冯毅雄, 金柯兵, 等. 基于无人机辅助与能量收集的移动边缘计算任务卸载优化[J]. 计算机集成制造系统, 2025, 31(10): 3541-3552.
Chen Xunyang, Feng Yixiong, Jin Kebing, et al. Optimization of task offloading in UAV-assisted mobile edge computing with energy harvesting[J]. Computer Integrated Manufacturing Systems, 2025, 31(10): 3541-3552.
|
| [25] |
Huang X W, Huang G F. Joint optimization of energy and task scheduling in wireless-powered IRS-assisted mobile-edge computing systems[J]. IEEE Internet of Things Journal, 2023, 10(12): 10997-11013. doi: 10.1109/JIOT.2023.3242951
|
| [26] |
Chen P C, Lyu B, Yang Z. Intelligent reflecting surface enhanced wireless powered mobile edge computing[C]//2021 IEEE/CIC International Conference on Communications in China (ICCC). Piscataway: IEEE, 2021: 1101-1106.
|
| [27] |
Zargari S, Hakimi A, Tellambura C, et al. Multiuser MISO PS-SWIPT systems: active or passive RIS?[J]. IEEE Wireless Communications Letters, 2022, 11(9): 1920-1924. doi: 10.1109/LWC.2022.3187671
|
| [28] |
Zou Y Z, Long Y S, Gong S M, et al. Robust beamforming optimization for self-sustainable intelligent reflecting surface assisted wireless networks[J]. IEEE Transactions on Cognitive Communications and Networking, 2022, 8(2): 856-870. doi: 10.1109/TCCN.2021.3133839
|
| [29] |
Li H, Xiong K, Dong R, et al. Joint active and passive beamforming in IRS-enhanced wireless powered MEC networks[J]. IEEE Wireless Communications Letters, 2022, 11(11): 2285-2289. doi: 10.1109/LWC.2022.3199693
|
| [30] |
Li S X, Duo B, Yuan X J, et al. Reconfigurable intelligent surface assisted UAV communication: joint trajectory design and passive beamforming[J]. IEEE Wireless Communications Letters, 2020, 9(5): 716-720. doi: 10.1109/LWC.2020.2966705
|
| [31] |
李翠然, 孙姝婧, 张泽鹏, 等. IRS辅助及人工噪声增强的高铁隐蔽通信波束赋形方法[J/OL]. 西南交通大学学报, 2025-01-02. https://kns.cnki.net/KCMS/detail/detail.aspx?filename=XNJT20241230009&dbname=CJFD&dbcode=CJFQ.
Li Cuiran, Sun Shujing, Zhang Zepeng, et al. IRS-assisted and artificial noise enhancement-based beamforming method in covert high-speed rail communications[J/OL]. Journal of Southwest Jiaotong University, 2025-01-02. https://kns.cnki.net/KCMS/detail/detail.aspx?filename=XNJT20241230009&dbname=CJFD&dbcode=CJFQ.
|
| [32] |
Boyd S, Vandenberghe L. Convex Optimization[M]. Cambridge: Cambridge University Press, 2004.
|
| [33] |
Shokri-Ghadikolaei H, Gkatzikis L, Fischione C. Beam-searching and transmission scheduling in millimeter wave communications[C]//2015 IEEE International Conference on Communications (ICC). Piscataway: IEEE, 2015: 1292-1297.
|
| [34] |
Lyu B, Ramezani P, Hoang D T, et al. Optimized energy and information relaying in self-sustainable IRS-empowered WPCN[J]. IEEE Transactions on Communications, 2021, 69(1): 619-633. doi: 10.1109/TCOMM.2020.3028875
|
| [35] |
Nguyen P X, Tran D H, Onireti O, et al. Backscatter-assisted data offloading in OFDMA-based wireless-powered mobile edge computing for IoT networks[J]. IEEE Internet of Things Journal, 2021, 8(11): 9233-9243. doi: 10.1109/JIOT.2021.3057360
|
| [36] |
Chu Z, Xiao P, Mi D, et al. A novel transmission policy for intelligent reflecting surface assisted wireless powered sensor networks[J]. IEEE Journal of Selected Topics in Signal Processing, 2021, 15(5): 1143-1158. doi: 10.1109/JSTSP.2021.3089423
|
| [37] |
Wu Q Q, Chen W, Ng D W K, et al. Spectral and energy-efficient wireless powered IoT networks: NOMA or TDMA?[J]. IEEE Transactions on Vehicular Technology, 2018, 67(7): 6663-6667. doi: 10.1109/TVT.2018.2799947
|
| [38] |
Chen G J, Wu Q Q, Chen W, et al. IRS-aided wireless powered MEC systems: TDMA or NOMA for computation offloading?[J]. IEEE Transactions on Wireless Communications, 2023, 22(2): 1201-1218. doi: 10.1109/TWC.2022.3203158
|
| [39] |
Zhou F H, Wu Y P, Hu R Q, et al. Computation rate maximization in UAV-enabled wireless-powered mobile-edge computing systems[J]. IEEE Journal on Selected Areas in Communications, 2018, 36(9): 1927-1941. doi: 10.1109/JSAC.2018.2864426
|
| [40] |
Liu B Y, Wan Y Y, Zhou F H, et al. Resource allocation and trajectory design for MISO UAV-assisted MEC networks[J]. IEEE Transactions on Vehicular Technology, 2022, 71(5): 4933-4948. doi: 10.1109/TVT.2022.3140833
|
| [41] |
Wu T Y, He H W, Shen H, et al. Energy-efficiency maximization for relay-aided wireless-powered mobile edge computing[J]. IEEE Internet of Things Journal, 2024, 11(10): 18534-18548. doi: 10.1109/JIOT.2024.3366982
|
| [42] |
Zhang Q, Zhao Y, Li H, et al. Joint optimization of STAR-RIS assisted UAV communication systems[J]. IEEE Wireless Communications Letters, 2022, 11(11): 2390-2394. doi: 10.1109/LWC.2022.3204353
|
| [43] |
Li X W, Xie Z, Chu Z, et al. Exploiting benefits of IRS in wireless powered NOMA networks[J]. IEEE Transactions on Green Communications and Networking, 2022, 6(1): 175-186. doi: 10.1109/TGCN.2022.3144744
|
| [44] |
Wu Q J, Cui M, Zhang G C, et al. Latency minimization for UAV-enabled URLLC-based mobile edge computing systems[J]. IEEE Transactions on Wireless Communications, 2024, 23(4): 3298-3311. doi: 10.1109/TWC.2023.3307154
|
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