Efficient design optimisation for UAV‐enabled mobile edge computing in cognitive radio networks. Issue 15 (1st September 2020)

• Record Type: Journal Article
• Authors: Pan, Yu; Da, Xinyu; Hu, Hang; Ni, Lei; Xu, Ruiyang; Zhang, Hongwei
• Is Part Of: IET communications. Volume 14:Issue 15(2020)
• Page Start: 2509
• Page End: 2515
• Publication Date: 2020-09-01
• Subjects: optimisation -- computational complexity -- cellular radio -- cognitive radio -- remotely operated vehicles -- autonomous aerial vehicles -- 5G mobile communication -- radio networks; cognitive radio networks -- wireless networks -- spectrum demand -- unmanned aerial vehicles -- UAV‐enabled mobile edge computing -- design optimisation -- WD‐UAV scheduling -- EE maximisation problem -- formulated optimisation problem -- wireless devices -- energy efficiency -- UAV‐enabled CR‐MEC framework -- partial offloading scheme -- local computation; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2019.1263
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : Mobile edge computing (MEC) has been envisaged as a promising technique in fifth generation (5G) and beyond wireless networks. In order to alleviate the explosive growth of computation and spectrum demand, cognitive radio (CR) and unmanned aerial vehicles (UAV) are studied in MEC‐aware networks. In this study, considering a local computation and partial offloading scheme, a UAV‐enabled CR‐MEC framework is proposed and the authors' aim is to maximise the energy efficiency (EE) of the wireless devices (WDs). The formulated optimisation problem is not convex and challenging to be solved. To deal with it, an equivalent reformulation of this EE maximisation problem is introduced, and the authors decompose the original problem into two sub‐problems, wherein the sub‐problems become tractable and can be solved by jointly optimising sensing time, offloading power and WD‐UAV scheduling. Numerical results highlight the EE enhancement with various system parameters and reveal the superiority of the proposed algorithm than other schemes with low computational complexity.