Energy Consumption Minimization in Secure Multi-antenna UAV-assisted MEC Networks with Channel Uncertainty
| العنوان: | Energy Consumption Minimization in Secure Multi-antenna UAV-assisted MEC Networks with Channel Uncertainty |
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| المؤلفون: | Weihao Mao, Ke Xiong, Yang Lu, Pingyi Fan, Zhiguo Ding |
| المصدر: | IEEE Transactions on Wireless Communications. :1-1 |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Signal Processing (eess.SP), FOS: Computer and information sciences, Information Theory (cs.IT), Computer Science - Information Theory, Applied Mathematics, FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing, Electrical and Electronic Engineering, Computer Science Applications |
| الوصف: | This paper investigates the robust and secure task transmission and computation scheme in multi-antenna unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) networks, where the UAV is dual-function, i.e., aerial MEC and aerial relay. The channel uncertainty is considered during information offloading and downloading. An energy consumption minimization problem is formulated under some constraints including users' quality of service and information security requirements and the UAV's trajectory's causality, by jointly optimizing the CPU frequency, the offloading time, the beamforming vectors, the artificial noise and the trajectory of the UAV, as well as the CPU frequency, the offloading time and the transmission power of each user. To solve the non-convex problem, a reformulated problem is first derived by a series of convex reformation methods, i.e., semi-definite relaxation, S-Procedure and first-order approximation, and then, solved by a proposed successive convex approximation (SCA)-based algorithm. The convergence performance and computational complexity of the proposed algorithm are analyzed. Numerical results demonstrate that the proposed scheme outperform existing benchmark schemes. Besides, the proposed SCA-based algorithm is superior to traditional alternative optimization-based algorithm. |
| تدمد: | 1558-2248 1536-1276 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9ce9d0a10b2e35bd21855e50ec7b6ba https://doi.org/10.1109/twc.2023.3248962 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....b9ce9d0a10b2e35bd21855e50ec7b6ba |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 15582248 15361276 |
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