UAV Data Collection Over NOMA Backscatter Networks: UAV Altitude and Trajectory Optimization

Abstract

The recent evolution of ambient backscattering technology has the potential to provide long-range and lowpower wireless communications. In this work, we study the unmanned aerial vehicle (UAV)-assisted backscatter networks where the UAV acts both as a mobile power transmitter and as an information collector. We aim to maximize the number of successfully decoded bits in the uplink while minimizing the UAV's flight time by optimizing its altitude. Power-domain NOMA scheme is employed in the uplink. An optimization framework is presented to identify the trade-off between numerous network parameters, such as UAV's altitude, number of backscatter devices, and backscatter coefficients. Numerical results show that an optimal altitude is computable for various network setups and that the impact of backscattering reflection coefficients on the maximum network throughput is significant. Based on this optimal altitude, we also show that an optimal trajectory plan is achievable.Index Terms-Internet of Things (IoT), Ambient backscattering, Unmanned Aerial Vehicle (UAV), Non-Orthogonal Multiple Access (NOMA).

A UAV-Enabled Wireless Powered Sensor Network Based on NOMA and Cooperative Relaying With Altitude Optimization

“…1, where a certain outdoor location is served by a single-antenna datacollecting UAV. The UAV is placed in an adjustable altitude H, aiming to collect the information from wireless powered sensor nodes located within the disk area with radius r C on the ground (e.g., [6], [34]). As shown in Fig.…”

Backscatter Wireless Communications and Sensing in Green Internet of Things

“…Content may change prior to final publication. Citation information: DOI 10.1109/TGCN.2021.3095792, IEEE Transactions on Green Communications and Networking [122] Single-UAV assisted BackCom Design an optimal trajectory for UAV Achieved optimal trajectory and data collection and enable uplink multiple access high decoding of data at the UAV [123] Multiple-UAV assisted BackCom Design techniques for minimum Achieved shortest operation time when data collection operating time of UAV using DRL maximum (four) UAVs were deployed [124] UAV assisted throughput Design an operating protocol Achieved high throughput gain enhancement for UAV as a relay [125] D2D-relaying assisted throughput Design an optimal policy for setting Improved BackCom network improvement operating condition for relay nodes throughput [126] QoS guaranty in UAV-assisted Design techniques to ensure UAV relaying Achieved higher arrival rate from BackCom based IoT through BackCom and multiple access IoT nodes and higher number of to guaranty QoS connected IoT nodes [127] IRS assisted BackCom Jointly optimize phase shifts at Reduced transmitter power at the the IRS and transmitter beamforming source and enhanced the tag's range [128] Intelligent coherent signal Develop unsupervised learning algorithm Achieved coherent detection detection at receiver for joint signal estimation and decoding with a low-cost receiver [129] Intelligent signal detection Exploit the clustering phenomenon Achieved non-coherent signal at receiver…”

Joint 3D Trajectory Design and Time Allocation for UAV-Enabled Wireless Power Transfer Networks

“…It should be noted that the coverage region of the UAV hovered at altitude h with the effective illumination angle 2Θ is a circle with radius h tan Θ [32]. Constraint (8) specifies the largest horizontal distance between UAV and the ERs that can not exceed the coverage radius of UAV.…”