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Conference Object Citation - WoS: 4Citation - Scopus: 6A Reinforcement Learning Algorithm for Data Collection in Uav-Aided Iot Networks With Uncertain Time Windows(Ieee, 2021) Cicek, Cihan TugrulUnmanned aerial vehicles (UAVs) have been considered as an efficient solution to collect data from ground sensor nodes in Internet-of-Things (IoT) networks due to their several advantages such as flexibility, quick deployment and maneuverability. Studies on this subject have been mainly focused on problems where limited UAV battery is introduced as a tight constraint that shortens the mission time in the models, which significantly undervalues the UAV potential. Moreover, the sensors in the network are typically assumed to have deterministic working times during which the data is uploaded. In this study, we revisit the UAV trajectory planning problem with a different approach and revise the battery constraint by allowing UAVs to swap their batteries at fixed stations and continue their data collection task, hence, the planning horizon can be extended. In particular, we develop a discrete time Markov process (DTMP) in which the UAV trajectory and battery swapping times are jointly determined to minimize the total data loss in the network, where the sensors have uncertain time windows for uploading. Due to the so-called curse-of-dimensionality, we propose a reinforcement learning (RL) algorithm in which the UAV is trained as an agent to explore the network. The computational study shows that our proposed algorithm outperforms two benchmark approaches and achieves significant reduction in data loss.Conference Object Miniaturized 2.4 Ghz Antenna Design for Uav Communication Link(Ieee, 2020) Yilmaz, Vadi Su; Kara, Ali; Aydin, ElifIn many communications applications, unlike conventional antennas, lightweight, flexible, small antennas that can adapt to mechanical and industrial constraints are required. In this study, the results of antenna design operating at 2.4 GHz are presented for use in Unmanned Aerial Vehicle (UAV) tele command links. In the parametric and optimization studies carried out on the antenna, it is aimed to increase the gain while keeping the size as small as possible. The requirements of the industry, such as light, aesthetics, miniature and high gain aspects of the antenna were targeted in the design process. Finally, an antenna of 55.2x88 mm size and 7dB gain was achieved using commercial electromagnetic design tools. The designed antenna become satisfying industrial requirements with these features.Conference Object Citation - WoS: 2Citation - Scopus: 5Low Radar Cross Section Uav Design in X-Band(Ieee, 2022) Unalir, Dizdar; Sezgin, Sila; Yuva, Cansu Sena; Yalcinkaya Gokdogan, Bengisu; Aydin, ElifAs Unmanned Aerial Vehicles (UAVs) have become widespread in defense industry, the radar technology that can detect them has also improved. These improvements cause UAVs to be detected more easily, which limits their effectiveness in military usage. Although the reduction of the radar cross-section (RCS) can provide a solution to this issue, the studies regarding that is insufficient in the literature. In this study, a shaping method is recommended to reduce the RCS of UAVs, and it is shown the method is effective to address the problem. Firstly, using a simulation tool, an UAV model is designed from simple shapes and the model is validated by comparing it with the ones in literature. Secondly, RCS values are measured using vertical and horizontal polarization throughout 360 degrees by incrementing the aspect angle by one degree in X-Band using the CST Studio Suite environment. Then, considering the hardware and aerodynamic requirements as well as limitations of the UAV model, a shaping technique is applied to the body, legs and the hollow parts of the UAV model with parametric simulations. The results show that the recommended shaping technique can provide a significant reduction in the RCS of an UAV.
