AoA-Based Positioning for Aerial Intelligent Reflecting Surface-Aided Wireless Communications: An Angle-Domain Approach

Author(s):  
Tao Zhou ◽  
Kui Xu ◽  
Zhexian Shen ◽  
Wei Xie ◽  
Dongmei Zhang ◽  
...  
2020 ◽  
Vol 68 (12) ◽  
pp. 7851-7866 ◽  
Author(s):  
Sheng Hong ◽  
Cunhua Pan ◽  
Hong Ren ◽  
Kezhi Wang ◽  
Arumugam Nallanathan

2021 ◽  
Author(s):  
Milad Tatar Mamaghani ◽  
Yi Hong

<div>Unmanned aerial vehicles (UAVs) are envisioned to be extensively employed for assisting wireless communications in Internet of Things (IoT). </div><div>On the other hand, terahertz (THz) enabled intelligent reflecting surface (IRS) is expected to be one of the core enabling technologies for forthcoming beyond-5G wireless communications that promise a broad range of data-demand applications. In this paper, we propose a UAV-mounted IRS (UIRS) communication system over THz bands for confidential data dissemination from an access point (AP) towards multiple ground user equipments (UEs) in IoT networks. Specifically, the AP intends to send data to the scheduled UE, while unscheduled UEs may behave as potential adversaries. To protect information messages and the privacy of the scheduled UE, we aim to devise an energy-efficient multi-UAV covert communication scheme, where the UIRS is for reliable data transmissions, and an extra UAV is utilized as a cooperative jammer generating artificial noise (AN) to degrade unscheduled UEs detection, improving communication covertness.</div><div>This poses a novel max-min optimization problem in terms of minimum average energy efficiency (mAEE), targetting to improve covert throughput and reduce UAVs' propulsion energy consumption subject to some practical constraints such as covertness which is determined analytically. Since the optimization problem is non-convex, we tackle it via the block successive convex approximation (BSCA) approach to iteratively solve a sequence of approximated convex sub-problems, designing the binary user scheduling, AP's power allocation, maximum AN jamming power, IRS beamforming, and both UAVs' trajectory and velocity planning. Finally, we present a low-complex overall algorithm for system performance enhancement with complexity and convergence analysis. Numerical results are provided to verify our analysis and demonstrate significant outperformance of our design over other existing benchmark schemes.</div>


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 86659-86673 ◽  
Author(s):  
Weiheng Jiang ◽  
Yu Zhang ◽  
Jinsong Wu ◽  
Wenjiang Feng ◽  
Yi Jin

Sign in / Sign up

Export Citation Format

Share Document