Autonomous Flying WiFi Access Point

Unmanned aerial vehicles (UAVs), aka drones, are widely used civil and commercial applications. A promising one is to use the drones as relying nodes to extend the wireless coverage. However, existing solutions only focus on deploying them to predefined locations. After that, they either remain stationary or only move in predefined trajectories throughout the whole deployment. In the open outdoor scenarios such as search and rescue or large music events, etc., users can move and cluster dynamically. As a result, network demand will change constantly over time and hence will require the drones to adapt dynamically. In this paper, we present a proof of concept implementation of an UAV access point (AP) which can dynamically reposition itself depends on the users movement on the ground. Our solution is to continuously keeping track of the received signal strength from the user devices for estimating the distance between users devices and the drone, followed by trilateration to localise them. This process is challenging because our on-site measurements show that the heterogeneity of user devices means that change of their signal strengths reacts very differently to the change of distance to the drone AP. Our initial results demonstrate that our drone is able to effectively localise users and autonomously moving to a position closer to them.

[1]  Wei Liu,et al.  Distance Measurement Model Based on RSSI in WSN , 2010, Wirel. Sens. Netw..

[2]  Taner Arsan,et al.  Received signal strength based least squares lateration algorithm for indoor localization , 2018, Comput. Electr. Eng..

[3]  So-Yeon Park,et al.  DroneNetX: Network Reconstruction Through Connectivity Probing and Relay Deployment by Multiple UAVs in Ad Hoc Networks , 2018, IEEE Transactions on Vehicular Technology.

[4]  Mi Zhou,et al.  Airborne WiFi networks through directional antennae: An experimental study , 2015, 2015 IEEE Wireless Communications and Networking Conference (WCNC).

[5]  Seng Wai Loke The Internet of Flying-Things: Opportunities and Challenges with Airborne Fog Computing and Mobile Cloud in the Clouds , 2015, ArXiv.

[6]  Qingqing Wu,et al.  Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks , 2017, IEEE Transactions on Wireless Communications.

[7]  Milos Doroslovacki,et al.  Prefetch-guard: Leveraging hardware prefetches to defend against cache timing channels , 2018, 2018 IEEE International Symposium on Hardware Oriented Security and Trust (HOST).

[8]  Damith C. Ranasinghe,et al.  TrackerBots: Autonomous UAV for Real-Time Localization and Tracking of Multiple Radio-Tagged Animals , 2022 .

[9]  Jeroen Wigard,et al.  Radio Channel Modeling for UAV Communication Over Cellular Networks , 2017, IEEE Wireless Communications Letters.

[10]  Sofie Pollin,et al.  LTE in the sky: trading off propagation benefits with interference costs for aerial nodes , 2016, IEEE Communications Magazine.

[11]  Mohammed Atiquzzaman,et al.  On the routing in Flying Ad Hoc Networks , 2015, 2015 Federated Conference on Computer Science and Information Systems (FedCSIS).

[12]  Joonhyuk Kang,et al.  Mobile Edge Computing via a UAV-Mounted Cloudlet: Optimization of Bit Allocation and Path Planning , 2016, IEEE Transactions on Vehicular Technology.

[13]  Huaiyu Dai,et al.  A Survey on Low Latency Towards 5G: RAN, Core Network and Caching Solutions , 2017, IEEE Communications Surveys & Tutorials.

[14]  Walid Saad,et al.  A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems , 2018, IEEE Communications Surveys & Tutorials.

[15]  Ismail Guvenc,et al.  Receding Horizon Multi-UAV Cooperative Tracking of Moving RF Source , 2017, IEEE Communications Letters.

[16]  Fazli Subhan,et al.  Indoor Child Tracking in Wireless Sensor Network using Fuzzy Logic Technique , 2011 .

[17]  Stephan Sand,et al.  Application-driven design of aerial communication networks , 2014, IEEE Communications Magazine.

[18]  Christian Bettstetter,et al.  Achieving air-ground communications in 802.11 networks with three-dimensional aerial mobility , 2013, 2013 Proceedings IEEE INFOCOM.

[19]  Miao Pan,et al.  IoT Enabled UAV: Network Architecture and Routing Algorithm , 2019, IEEE Internet of Things Journal.

[20]  Ismail Güvenç,et al.  Localization of WiFi Devices Using Probe Requests Captured at Unmanned Aerial Vehicles , 2017, 2017 IEEE Wireless Communications and Networking Conference (WCNC).

[21]  Rui Zhang,et al.  Wireless communications with unmanned aerial vehicles: opportunities and challenges , 2016, IEEE Communications Magazine.

[22]  Ismail Güvenç,et al.  Indoor UAV Navigation to a Rayleigh Fading Source Using Q-Learning , 2017, ArXiv.

[23]  Xing Zhang,et al.  Radio network-aware edge caching for video delivery in MEC-enabled cellular networks , 2018, 2018 IEEE Wireless Communications and Networking Conference Workshops (WCNCW).