scholarly journals Optimization of Unmanned Aerial Vehicle Augmented Ultra-Dense Networks

2020 ◽  
Author(s):  
Alireza Zamani ◽  
Robert Kämmer ◽  
Yulin Hu ◽  
Anke Schmeink
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Optimization Problem ◽  
Original Problem ◽  
Heuristic Method ◽  
Linear Structure ◽  
Small Cells ◽  
Simulation Studies ◽  
Dense Networks ◽  
Aerial Vehicle ◽  
Lower Complexity

Abstract In this paper, we study the integration of unmanned aerial vehicle small cells (UAV-SC) for the purpose of augmenting or temporarily restoring service to an ultra-dense cellular network. The aim is to minimize the overall power consumption of the network by jointly optimizing the number of UAV-SCs, their placement, associations and the power allocation, subject to user QoS, transmit power and fronthaul capacity constraints. As the resulting optimization problem is non-convex and computationally inefficient to solve, we investigate lower complexity alternatives. By reformulating the original problem, a linear structure can be obtained that is efficiently solved by off-the-shelf solvers. Furthermore, we also propose a meta-heuristic method that is based on particle swarm optimization. The performance of the proposed methods is evaluated via simulation studies and compared to state-of-the-art techniques. The results illustrate that the proposed methods consistently outperform conventional techniques by deploying fewer UAV-SCs and also lowering the transmit powers. Furthermore, considerable power savings were observed particularly for low QoS demands and dense scenarios.

scholarly journals Optimization of unmanned aerial vehicle augmented ultra-dense networks

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Alireza Zamani ◽  
Robert Kämmer ◽  
Yulin Hu ◽  
Anke Schmeink
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Original Problem ◽  
Heuristic Method ◽  
Linear Structure ◽  
Small Cells ◽  
Simulation Studies ◽  
Dense Networks ◽  
Aerial Vehicle ◽  
Lower Complexity

Abstract In this paper, we study the integration of unmanned aerial vehicle small cells (UAV-SCs) for the purpose of augmenting or temporarily restoring service to an ultra-dense cellular network. The aim is to minimize the overall power consumption of the network by jointly optimizing the number of UAV-SCs, their placement, associations, and the power allocation, subject to user QoS (quality of service), transmit power, and fronthaul capacity constraints. As the resulting optimization problem is non-convex and computationally inefficient to solve, we investigate lower complexity alternatives. By reformulating the original problem, a linear structure can be obtained that is efficiently solved by off-the-shelf solvers. Furthermore, we also propose a meta-heuristic method that is based on particle swarm optimization. The performance of the proposed methods is evaluated via simulation studies and compared to state-of-the-art techniques. The results illustrate that the proposed methods consistently outperform conventional techniques by deploying fewer UAV-SCs and also lowering the transmit powers. Furthermore, considerable power savings were observed particularly for low QoS demands and dense scenarios.

scholarly journals A low-cost solution for unmanned aerial vehicle navigation in a global positioning system–denied environment

2018 ◽  
Vol 14 (6) ◽  
pp. 155014771878175 ◽  
Author(s):  
Shahrukh Ashraf ◽  
Priyanka Aggarwal ◽  
Praveen Damacharla ◽  
Hong Wang ◽  
Ahmad Y Javaid ◽  
...  
Keyword(s):  
Optical Flow ◽  
Unmanned Aerial Vehicle ◽  
Global Positioning System ◽  
Motion Vector ◽  
Block Matching ◽  
Positioning System ◽  
Simulation Studies ◽  
Flow Measurements ◽  
Global Positioning ◽  
Aerial Vehicle

The ability of an autonomous unmanned aerial vehicle to navigate and fly precisely determines its utility and performance. The current navigation systems are highly dependent on the global positioning system and are prone to error because of global positioning system signal outages. However, advancements in onboard processing have enabled inertial navigation algorithms to perform well during short global positioning system outages. In this article, we propose an intelligent optical flow–based algorithm combined with Kalman filters to provide the navigation capability during global positioning system outages and global positioning system–denied environments. Traditional optical flow measurement uses block matching for motion vector calculation that makes the measurement task computationally expensive and slow. We propose the application of an artificial bee colony–based block matching technique for faster optical flow measurements. To effectively fuse optical flow data with inertial sensors output, we employ a modified form of extended Kalman filter. The modifications make the filter less noisy by utilizing the redundancy of sensors. We have achieved an accuracy of ~95% for all non-global positioning system navigation during our simulation studies. Our real-world experiments are in agreement with the simulation studies when effects of wind are taken into consideration.

scholarly journals An Improved Equilibrium Optimizer with Application in Unmanned Aerial Vehicle Path Planning

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1814
Author(s):  
An-Di Tang ◽  
Tong Han ◽  
Huan Zhou ◽  
Lei Xie
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicle ◽  
Optimization Problem ◽  
Fitness Function ◽  
Population Diversity ◽  
Planning Problem ◽  
Turn Angle ◽  
Set Constraints ◽  
Planning Algorithm ◽  
Aerial Vehicle

The unmanned aerial vehicle (UAV) path planning problem is a type of complex multi-constraint optimization problem that requires a reasonable mathematical model and an efficient path planning algorithm. In this paper, the fitness function including fuel consumption cost, altitude cost, and threat cost is established. There are also four set constraints including maximum flight distance, minimum flight altitude, maximum turn angle, and maximum climb angle. The constrained optimization problem is transformed into an unconstrained optimization problem by using the penalty function introduced. To solve the model, a multiple population hybrid equilibrium optimizer (MHEO) is proposed. Firstly, the population is divided into three subpopulations based on fitness and different strategies are executed separately. Secondly, a Gaussian distribution estimation strategy is introduced to enhance the performance of MHEO by using the dominant information of the populations to guide the population evolution. The equilibrium pool is adjusted to enhance population diversity. Furthermore, the Lévy flight strategy and the inferior solution shift strategy are used to help the algorithm get rid of stagnation. The CEC2017 test suite was used to evaluate the performance of MHEO, and the results show that MHEO has a faster convergence speed and better convergence accuracy compared to the comparison algorithms. The path planning simulation experiments show that MHEO can steadily and efficiently plan flight paths that satisfy the constraints, proving the superiority of the MHEO algorithm while verifying the feasibility of the path planning model.

scholarly journals Improving the efficiency of the powerplant of an unmanned aerial vehicle through the use of cryogenic fuel

2020 ◽  
Vol 19 (3) ◽  
pp. 7-17
Author(s):  
A. S. Kolesnikov ◽  
T. V. Grasko ◽  
V. V. Raznoschikov
Keyword(s):  
Power Plant ◽  
Unmanned Aerial Vehicle ◽  
Optimization Problem ◽  
Integrated Approach ◽  
Working Process ◽  
Flight Duration ◽  
Fuel Tanks ◽  
Aerial Vehicle ◽  
Significant Achievement ◽  
High Level

The article is devoted to increasing the efficiency of the power plant of an unmanned aerial vehicle through the use of cryogenic fuel. It has been substantiated that the creation of a power plant is based on an integrated approach to the Aircraft Power Plant Fuel system and ensures a significant achievement of perfection indicators according to high-level criteria (fuel consumption per hour (kilometer), range, flight duration, etc.) Analysis of energetic properties of some types of aviation fuels showed that gas fuels in their properties are generally superior to liquid ones, except for one thing low density, which requires a large volume of fuel tanks. An unmanned aerial vehicle Tu-143 Reis (Flight) equipped with a pure turbojet engine TR3-117 was chosen as a prototype. The optimization problem of the study was solved. The task was to determine if an engine intended to run on kerosene could operate on propane according to the main parameters of the working process, provided that possible flight conditions were maintained. The obtained altitude and speed characteristics indicate that the conversion of engines from kerosene to cryogenic propane is possible without changing their design by modernizing the combustion chamber and individual elements of the automatic fuel metering system.

A UAV Trajectory Planning Algorithm for Simultaneous Search and Track

2005 ◽  
Author(s):  
John Tisdale ◽  
J. Karl Hedrick
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Constant Velocity ◽  
A Priori ◽  
Heuristic Method ◽  
Reachability Graph ◽  
Planning Algorithm ◽  
Aerial Vehicle ◽  
Target Path ◽  
Areas Of Interest ◽  
Turn Rate

This paper considers trajectories for an unmanned aerial vehicle (UAV) that must search an area while tracking a target. The UAV has a constrained turn rate and a constant velocity; it is assumed that there are certain areas of interest that have a higher search value than others. An algorithm is presented that seeks to maximize the value of the area searched while still maintaining the track. The problem is discretized in both time and the control; the motion of the UAV is constrained to the reachability graph, a subset of the forward reachable set. At each revisit, the target path is estimated for the next revisit. A heuristic method is used to determine the best UAV path, because the target path is not known a priori. Feasible paths are found by examining the terminating vertices of the reachability graph. A cooperative implementation, for a team of UAVs patrolling the same region, is developed. Simulation indicates the feasibility of the method for a real-time implementation. Trajectories for example scenarios are presented and discussed.

Study on Fault Diagnosis of Planetary Gearbox in Unmanned Aerial Vehicle Using Multi sensor Data

2020 ◽  
Vol 20 (4) ◽  
pp. 332-342
Author(s):  
Hyung Jun Park ◽  
Seong Hee Cho ◽  
Kyung-Hwan Jang ◽  
Jin-Woon Seol ◽  
Byung-Gi Kwon ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Unmanned Aerial Vehicle ◽  
Sensor Data ◽  
Planetary Gearbox ◽  
Aerial Vehicle

Results of Spatial Structure of Atmosphere Radiation in a Spectral Range (1.5–2) µm Research

2018 ◽  
pp. 7-13
Author(s):  
Anton M. Mishchenko ◽  
Sergei S. Rachkovsky ◽  
Vladimir A. Smolin ◽  
Igor V . Yakimenko
Keyword(s):  
Spatial Structure ◽  
Unmanned Aerial Vehicle ◽  
Wavelength Range ◽  
Spectral Range ◽  
Near Ir ◽  
Optoelectronic Systems ◽  
Aerial Vehicle

Results of experimental studying radiation spatial structure of atmosphere background nonuniformities and of an unmanned aerial vehicle being the detection object are presented. The question on a possibility of its detection using optoelectronic systems against the background of a cloudy field in the near IR wavelength range is also considered.

Sign in / Sign up

Export Citation Format

Share Document