UAV Trajectory optimization for Data-Gathering from Backscattering Sensor Networks

Yeh, Shih-Huan; Wang, Yung-Shun; Perera, Tharindu D. Ponnimbaduge; Hong, Yang; Jayakody, Dushantha Nalin K.

doi:10.1109/icc40277.2020.9148756

Cited by 12 publications

(3 citation statements)

References 16 publications

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“…From the figure, it can be observed that as the distance increases the AAoI increases exponentially for different data rates. Transmission techniques like power allocation, beamforming, receiver algorithms, and UAV trajectory optimization [29] can be used to optimize AAoI in this scenario.…”

Section: Resultsmentioning

confidence: 99%

An intelligent age of information based self‐energized UAV‐assisted wireless communication system

Jeganathan,

Dhayabaran,

Jayakody

et al. 2023

IET Communications

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Internet‐of‐things is an enabling technology in the fourth‐generation industrial revolution. The freshness of the data sent by a sensor node (SN) is an important parameter in the Internet‐of‐things, unlike the throughput in cellular communications. A relatively new performance metric named age of information (AoI) is used in this paper to quantify the freshness of the data. The SN, located in the transport infrastructure, harvests energy from radio frequency signals transmitted by the FD‐UAV. This is used to transmit real‐time sensor observations to the data sink via FD‐UAV. The SN generates an update after replenishing the battery and transmits it by using the harvested energy. A closed‐form expression for average AoI is derived as a function of time allocated for energy harvesting. The optimal time allocation for energy harvesting that maximizes the freshness of data update is identified. A deep learning technique namely long‐short term memory is used to predict the average AoI. Simulation results demonstrate the usefulness of the performance bounds in terms of the freshness of data updates.

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Section: Resultsmentioning

confidence: 99%

An intelligent age of information based self‐energized UAV‐assisted wireless communication system

Jeganathan,

Dhayabaran,

Jayakody

et al. 2023

IET Communications

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“…In parallel, some research efforts have been directed towards improving the fidelity of the data collected in such semi-passive setups [26], [28], [30], [31]. These works aimed at minimizing the age of information, mean square error of the sensors reconstructed observations, maximizing the ratio between number of correctly decoded bits and the flighttime duration to collect the sensors data, and maximizing the uplink fair-secrecy-rate in the presence of a multitude of eavesdroppers.…”

Section: Introductionmentioning

confidence: 99%

Laser-Empowered UAVs for Aerial Data Aggregation in Passive IoT Networks

Abdelhady,

Celik,

Diaz-Vilor

et al. 2024

IEEE Open J. Commun. Soc.

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This paper investigates the maximization of data harvested by an uncrewed aerial vehicle (UAV) that supports Internet of Things (IoT) deployment scenarios. The novelty of the paper is that we study the feasibility of battery-free UAV and IoT device deployment where the UAV is powered by a ground laser source, and the IoT devices are powered by a power beacon via bistatic backscattering. We aim to optimize the UAV trajectory while minimizing the laser energy consumption throughout the entire flight by tuning the laser power and the power beacon radiated temporal power profiles. Upon considering an unspecified flying time, we adopt path discretization and resort to the single-block successive convex approximation (SCA) to solve the data collection maximization problem. In addition to considering the UAV dynamics and power budget, two novel SCA-compatible bounds are introduced for the product of positive mixed convex/concave functions. Finally, the simulation results show that the proposed algorithm increases the data collected under different operation conditions by approximately 90%.

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“…Complementarily, some research efforts were dedicated towards improving the fidelity of the collected data in such semi-passive setups [28], [30], [32], [33]. These works aimed at minimizing the age of information, mean square error of the sensors reconstructed observations, maximizing the ratio between number of correctly decoded bits and the flight time duration to collect the sensors data, and maximizing the uplink fair-secrecy-rate in the presence of a multitude of eavesdroppers.…”

Section: Introductionmentioning

confidence: 99%

On the Optimization of Laser-Powered UAV-Assisted Backscatter Communications

Abd‐Elhady¹,

Diaz-Vilor²,

Çelik³

et al. 2022

Preprint

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<p>This paper studies the joint trajectory and resource allocation problem for a laser-powered unmanned aerial vehicle (UAV) assisted data aggregation framework. The considered system incorporates semi-passive nodes that establish their wireless communication links with the UAV via bistatic backscatter communications enabled by a battery-powered power beacon source. We aim to optimize the UAV trajectory while minimizing the laser energy consumption throughout the whole flight by tuning the laser power and the power beacon radiated temporal power profiles. Towards this aim, we first adopt path discretization to approximate the optimal control problem of interest into a non-linear programming one whilst accounting for the UAV dynamics constraints and available power budget restrictions. Then, we solve the problem by successive convex approximation (SCA) over the joint set of variables and determine the problem feasibility by a data collection maximization problem. Moreover, we propose a low-complexity solution for the feasibility problem. Finally, the conducted simulations show that the proposed algorithm provides 50% collected data increase and almost 50% laser energy reduction under different operation conditions such as laser station position, maximum laser output power, start and end points of the trajectory, power beacon battery capacity, and the permissible flight length.</p>

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UAV Trajectory optimization for Data-Gathering from Backscattering Sensor Networks

Cited by 12 publications

References 16 publications

An intelligent age of information based self‐energized UAV‐assisted wireless communication system

An intelligent age of information based self‐energized UAV‐assisted wireless communication system

Laser-Empowered UAVs for Aerial Data Aggregation in Passive IoT Networks

On the Optimization of Laser-Powered UAV-Assisted Backscatter Communications

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