scholarly journals Performance Optimization in UAV-Assisted Wireless Powered mmWave Networks for Emergency Communications

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Jinsong Gui ◽  
Nansen Jin ◽  
Xiaoheng Deng
Keyword(s):  
Performance Optimization ◽  
Optimization Problem ◽  
Optimal Path ◽  
Capacity Utilization ◽  
Base Station ◽  
Radio Access ◽  
Battery Capacity ◽  
Access Service ◽  
Aerial Vehicle ◽  
Rotary Wing

In this paper, we explore how a rotary-wing unmanned aerial vehicle (UAV) acts as an aerial millimeter wave (mmWave) base station to provide recharging service and radio access service in a postdisaster area with unknown user distribution. The addressed optimization problem is to find out the optimal path starting and ending at the same recharging point to cover a wider area under limited battery capacity, and it can be transformed to an extended multiarmed bandit (MAB) problem. We propose the two improved path planning algorithms to solve this optimization problem, which can improve the ability to explore the unknown user distribution. Simulation results show that, in terms of the total number of served user equipment (UE), the number of visited grids, the amount of data, the average throughput, and the battery capacity utilization level, one of our algorithms is superior to its corresponding comparison algorithm, while our other algorithm is superior to its corresponding comparison algorithm in terms of the number of visited grids.

scholarly journals Energy Efficiency Optimization of Cognitive UAV-Assisted Edge Communication for Semantic Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yilong Gu ◽  
Yangchao Huang ◽  
Hang Hu ◽  
Weiting Gao ◽  
Yu Pan
Keyword(s):  
Energy Efficiency ◽  
Internet Of Things ◽  
Energy Efficient ◽  
Optimization Problem ◽  
Optimization Scheme ◽  
Battery Capacity ◽  
Aerial Vehicle ◽  
Efficient Alternative ◽  
The Internet Of Things

With the consolidation of the Internet of Things (IoT), the unmanned aerial vehicle- (UAV-) based IoT has attracted much attention in recent years. In the IoT, cognitive UAV can not only overcome the problem of spectrum scarcity but also improve the communication quality of the edge nodes. However, due to the generation of massive and redundant IoT data, it is difficult to realize the mutual understanding between UAV and ground nodes. At the same time, the performance of the UAV is severely limited by its battery capacity. In order to form an autonomous and energy-efficient IoT system, we investigate semantically driven cognitive UAV networks to maximize the energy efficiency (EE). The semantic device model for cognitive UAV-assisted IoT communication is constructed. And the sensing time, the flight speed of UAV, and the coverage range of UAV communication are jointly optimized to maximize the EE. Then, an efficient alternative algorithm is proposed to solve the optimization problem. Finally, we provide computer simulations to validate the proposed algorithm. The performance of the joint optimization scheme based on the proposed algorithm is compared to some benchmark schemes. And the simulation results show that the proposed scheme can obtain the optimal system parameters and can significantly improve the EE.

scholarly journals UAV Assisted Wireless Network

2021 ◽  
Vol 2078 (1) ◽  
pp. 012022
Author(s):  
Sihao Teng
Keyword(s):  
Energy Efficiency ◽  
Wireless Network ◽  
Network Performance ◽  
High Efficiency ◽  
Base Station ◽  
Iteration Algorithm ◽  
Flight Trajectory ◽  
Battery Capacity ◽  
Aerial Vehicle ◽  
Increasing Demand

Abstract With the increasing demand of social network service, the unmanned aerial vehicle has been used as a base station to assist terrestrial base station to improve wireless network performance. UAV base station provides high efficiency and wider data transmitting range due to the small size and flexibility of UAV. However, UAV wireless network faces few challenges. Energy efficiency is hard to achieve due to small battery capacity. The base station performance is also very important. It can be determined by aircraft’s flying stability, the performance of air to ground communication and the limitation of wireless coverage of UAV. In order to achieve optimal UAV deployment, improving deployment delay, communication coverage and UAV number limitation are important. Trajectory optimizing problems also need to be considered. This article analyzes UAV assisted wireless networks through investigating UAV energy efficiency, UAV aided network performance, optimal deployment methods and flight trajectory. It is shown that energy efficiency can be optimized by applying LoS based channel in UAV trajectory planning. And inequality iteration algorithm proposed by former researchers is used to determine optimal flight trajectory. This method is efficient because of cellular network’s interference-free ability. As for performance, channel selection methods are used to reduce overflow rate and boost data-received size. These methods are analyzed and proved to be effective for improving UAV aided wireless network performance.

Fair Deployment of an Unmanned Aerial Vehicle Base Station for Maximal Coverage

2019 ◽  
Vol E102.B (10) ◽  
pp. 2014-2020
Author(s):  
Yancheng CHEN ◽  
Ning LI ◽  
Xijian ZHONG ◽  
Yan GUO
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Base Station ◽  
Aerial Vehicle

scholarly journals SWIPT in mMIMO system with non-linear energy-harvesting terminals: protocol design and performance optimization

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Kui Xu ◽  
Ming Zhang ◽  
Jie Liu ◽  
Nan Sha ◽  
Wei Xie ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Performance Optimization ◽  
Power Transmission ◽  
Base Station ◽  
Second Phase ◽  
Wireless Power ◽  
Half Duplex ◽  
Non Linear ◽  
Two Phases ◽  
And Performance

Abstract In this paper, we design the simultaneous wireless information and power transfer (SWIPT) protocol for massive multi-input multi-output (mMIMO) system with non-linear energy-harvesting (EH) terminals. In this system, the base station (BS) serves a set of uplink fixed half-duplex (HD) terminals with non-linear energy harvester. Considering the non-linearity of practical energy-harvesting circuits, we adopt the realistic non-linear EH model rather than the idealistic linear EH model. The proposed SWIPT protocol can be divided into two phases. The first phase is designed for terminals EH and downlink training. A beam domain energy beamforming method is employed for the wireless power transmission. In the second phase, the BS forms the two-layer receive beamformers for the reception of signals transmitted by terminals. In order to improve the spectral efficiency (SE) of the system, the BS transmit power- and time-switching ratios are optimized. Simulation results show the superiority of the proposed beam-domain SWIPT protocol on SE performance compared with the conventional mMIMO SWIPT protocols.

scholarly journals Robust Beamforming Design for Secure V2X Downlink System with Wireless Information and Power Transfer under a Nonlinear Energy Harvesting Model

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3294 ◽  
Author(s):  
Shidang Li ◽  
Chunguo Li ◽  
Weiqiang Tan ◽  
Baofeng Ji ◽  
Luxi Yang
Keyword(s):  
Energy Harvesting ◽  
Traffic Safety ◽  
Optimization Problem ◽  
Optimal Solution ◽  
Base Station ◽  
Power Splitting ◽  
Power Transfer ◽  
Vehicular Communication ◽  
Downlink System ◽  
Nonlinear Energy

Vehicle to everything (V2X) has been deemed a promising technology due to its potential to achieve traffic safety and efficiency. This paper considers a V2X downlink system with a simultaneous wireless information and power transfer (SWIPT) system where the base station not only conveys data and energy to two types of wireless vehicular receivers, such as one hybrid power-splitting vehicular receiver, and multiple energy vehicular receivers, but also prevents information from being intercepted by the potential eavesdroppers (idle energy vehicular receivers). Both the base station and the energy vehicular receivers are equipped with multiple antennas, whereas the information vehicular receiver is equipped with a single antenna. In particular, the imperfect channel state information (CSI) and the practical nonlinear energy harvesting (EH) model are taken into account. The non-convex optimization problem is formulated to maximize the minimum harvested energy power among the energy vehicular receivers satisfying the lowest harvested energy power threshold at the information vehicular receiver and secure vehicular communication requirements. In light of the intractability of the optimization problem, the semidefinite relaxation (SDR) technique and variable substitutions are applied, and the optimal solution is proven to be tight. A number of results demonstrate that the proposed robust secure beamforming scheme has better performance than other schemes.

Proportional Navigation (PN) Based Tracking of Ground Targets by Quadrotor UAVs

2013 ◽  
Author(s):  
Ruoyu Tan ◽  
Manish Kumar
Keyword(s):  
Target Tracking ◽  
Proportional Navigation ◽  
Tracking Method ◽  
Maneuvering Targets ◽  
Time Optimal ◽  
Aerial Vehicle ◽  
Quadrotor Uavs ◽  
The One ◽  
Rotary Wing ◽  
Guidance Laws

This paper addresses the problem of controlling a rotary wing Unmanned Aerial Vehicle (UAV) tracking a target moving on ground. The target tracking problem by UAVs has received much attention recently and several techniques have been developed in literature most of which have been applied to fixed wing aircrafts. The use of quadrotor UAVs, the subject of this paper, for target tracking presents several challenges especially for highly maneuvering targets since the development of time-optimal controller (required if target is maneuvering fast) for quadrotor UAVs is extremely difficult due to highly non-linear dynamics. The primary contribution of this paper is the development of a proportional navigation (PN) based method and its implementation on quad-rotor UAVs to track moving ground target. The PN techniques are known to be time-optimal in nature and have been used in literature for developing guidance systems for missiles. There are several types of guidance laws that come within the broad umbrella of the PN method. The paper compares the performance of these guidance laws for their application on quadrotors and chooses the one that performs the best. Furthermore, to apply this method for target tracking instead of the traditional objective of target interception, a switching strategy has also been designed. The method has been compared with respect to the commonly used Proportional Derivative (PD) method for target tracking. The experiments and numerical simulations performed using maneuvering targets show that the proposed tracking method not only carries out effective tracking but also results into smaller oscillations and errors when compared to the widely used PD tracking method.

scholarly journals A Heuristic Evolutionary Algorithm of UAV Path Planning

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Zhangjie Fu ◽  
Jingnan Yu ◽  
Guowu Xie ◽  
Yiming Chen ◽  
Yuanhang Mao
Keyword(s):  
Energy Consumption ◽  
Evolutionary Algorithm ◽  
Rapid Development ◽  
Optimal Path ◽  
Battery Life ◽  
Intelligent Robot ◽  
Urgent Problem ◽  
Intelligent Robots ◽  
Aerial Vehicle ◽  
The Cost

With the rapid development of the network and the informatization of society, how to improve the accuracy of information is an urgent problem to be solved. The existing method is to use an intelligent robot to carry sensors to collect data and transmit the data to the server in real time. Many intelligent robots have emerged in life; the UAV (unmanned aerial vehicle) is one of them. With the popularization of UAV applications, the security of UAV has also been exposed. In addition to some human factors, there is a major factor in the UAV’s endurance. UAVs will face a problem of short battery life when performing flying missions. In order to solve this problem, the existing method is to plan the path of UAV flight. In order to find the optimal path for a UAV flight, we propose three cost functions: path security cost, length cost, and smoothness cost. The path security cost is used to determine whether the path is feasible; the length cost and smoothness cost of the path directly affect the cost of the energy consumption of the UAV flight. We proposed a heuristic evolutionary algorithm that designed several evolutionary operations: substitution operations, crossover operations, mutation operations, length operations, and smoothness operations. Through these operations to enhance our build path effect. Under the analysis of experimental results, we proved that our solution is feasible.

scholarly journals Optimal Sensor Association and Data Collection in Power Materials Warehouse Based on Internet of Things

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7449
Author(s):  
Fangqiuzi He ◽  
Junfeng Xu ◽  
Jinglin Zhong ◽  
Guang Chen ◽  
Shixin Peng
Keyword(s):  
Internet Of Things ◽  
Optimization Problem ◽  
Ant Colony Algorithm ◽  
Cluster Head ◽  
Descent Method ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Upper And Lower Bounds ◽  
Battery Capacity ◽  
Intelligent Management

In order to realize the intelligent management of a power materials warehouse, the Internet of Things based on wireless sensor networks (WSNs) is a promising effective solution. Considering the limited battery capacity of sensor nodes, the optimization of the topology control and the determination of the amount of collected data are critical for prolonging the survival time of WSNs and increasing the satisfaction of the warehouse supplier. Therefore, in this paper, an optimization problem on sensor association and acquisition data satisfaction is proposed, and the subproblem of the sensor association is modeled as the knapsack problem. To cope with it, the block coordinate descent method is used to obtain the suboptimal solution. A sensor association scheme based on the ant colony algorithm (ACO) is proposed, and the upper and lower bounds of this optimization problem are also obtained. After this, a cluster head selection algorithm is given to find the optimal cluster head. Finally, the experimental simulations show that the algorithms proposed in this paper can effectively improve the energy utilization of WSNs to ensure the intelligent management of a power materials warehouse.

scholarly journals Grid based Energy-Efficient Cross-Layer Optimization Model in WSN Using Dual Mobile Sinks

2021 ◽  
Author(s):  
Vimala D ◽  
Manikandan K
Keyword(s):  
Network Lifetime ◽  
Optimization Model ◽  
Energy Efficient ◽  
Simulation Analysis ◽  
Optimal Path ◽  
Maximum Energy ◽  
Base Station ◽  
Cross Layer ◽  
Cross Layer Optimization ◽  
Grid Based

Abstract In recent days, wireless sensor network (WSN) gained more attention among researchers as well as industries. It is composed with massive number of sensors which are independently organized cooperate with one another for collecting, processing and transmitting data to the base station (BS) or sink. Since sensors undergo random deployment in harsh environment, it is difficult or not even possible to replace the batteries. So, energy efficient clustering and routing techniques are preferable to reduce the dissipation of energy and improve the network lifetime. This paper introduces a new Grid based Energy-Efficient Cross-Layer Optimization Model in WSN Using Dual Mobile Sink (GEECLO). The proposed method involves three main processes namely grid partitioning, clustering and routing. Initially, the entire network is partitioned into different zones and then sub zones. Then, type II FL process gets executed to select the CHs and construct the clusters. Finally, dolphin swarm optimization algorithm (DSOA) based routing process takes place to select the optimal path for inter-cluster communication. A detailed simulation analysis takes place to ensure the betterment of the GEECLO algorithm. The obtained experimentation outcome depicted that the GEECLO model offers maximum energy efficiency and network lifetime.

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