Aerial networks, composed of Unmanned Aerial Vehicles (UAVs) acting as Wi-Fi access points or cellular base stations, are emerging as an interesting solution to provide on-demand wireless connectivity to users, when there is no network infrastructure available, or to enhance the network capacity. This article proposes a traffic-aware topology control solution for aerial networks that holistically combines the placement of UAVs with a predictive and centralized routing protocol. The synergy created by the combination of the UAV placement and routing solutions allows the aerial network to seamlessly update its topology according to the users' traffic demand, whilst minimizing the disruption caused by the movement of the UAVs. As a result, the Quality of Service (QoS) provided to the users is improved. The components of the proposed solution are described and evaluated individually in this article by means of simulation and an experimental testbed. The results show that all the components improve the QoS provided to the users when compared to the corresponding baseline solutions.
This paper studies the improvement of the achievable end-to-end data rate of ground users assisted with unmanned aerial vehicles (UAVs) and tethered balloons (TBs). The goal is to maximize the end-to-end throughput of a network suffering from the absence of terrestrial infrastructure. First, we solve an integer linear programming problem to optimize the associations. Then, we solve the UAVs transmit powers optimally by converting the problem into a convex one. Subsequently, an efficient algorithm is proposed to optimize the UAVs placement. Finally, our mathematical formalism is illustrated wit…
As an autonomous vehicles, Unmanned Aerial Vehicles (UAVs) are subjected to several challenges. One of the challenges is for UAV to be able to avoid collision. Many collision avoidance methods have been proposed to address this issue. Furthermore, in a multi-UAV system, it is also important to address communication issue among UAVs for cooperation and collaboration. This issue can be addressed by setting up an ad-hoc network among UAVs. There is also a need to consider the challenges in the deployment of UAVs, as well as, in the development of collision avoidance methods and the establishment …
Unmanned Aerial Vehicles (UAVs) acting as Flying Access Points (FAPs) are being used to provide on-demand wireless connectivity in extreme scenarios. Despite ongoing research, the optimization of UAVs' positions according to dynamic users' traffic demands remains challenging. We propose the Traffic-aware UAV Placement Algorithm (TUPA), which positions a UAV acting as FAP according to the users' traffic demands, in order to maximize the network utility. Using a DRL approach enables the FAP to autonomously learn and adapt to dynamic conditions and requirements of networking scenarios. Moreover, …
Beyond visual line-of-sight connectivity is key for use cases of unmanned aerial vehicles (UAVs) such as package delivery, infrastructure inspection, and rescue missions. Cellular networks stand ready to support flying UAVs by providing wide-area, quality, and secure connectivity for UAV operations. Ensuring reliable connections in the presence of UAV movements is important for safety control and operations of UAVs. With increasing height above the ground, the radio environment changes. Using terrestrial cellular networks to provide connectivity to the UAVs moving in the sky may face new chall…
This paper considers an aerial base station (aerial-BS) assisted terrestrial network where user mobility is taken into account. User movement changes the network dynamically which may result in performance loss. To avoid this loss, guarantee a minimum quality-of-service (QoS) and possibly increase the QoS, we add an aerial-BS to the network. For a fair comparison between the conventional terrestrial network and the aerial-BS assisted one, we keep the total number of BSs identical in both networks. Obtaining the best performance in such networks highly depends on the optimal placement of the ae…
The application domains of civilian unmanned aerial systems (UASs) include agriculture, exploration, transportation, and entertainment. The expected growth of the UAS industry brings along new challenges: Unmanned aerial vehicle (UAV) flight control signaling requires low throughput, but extremely high reliability, whereas the data rate for payload data can be significant. This paper develops UAV number projections and concludes that small and micro UAVs will dominate the US airspace with accelerated growth between 2028 and 2032. We analyze the orthogonal frequency division multiplexing (OFDM)…
Unmanned Aerial Vehicles (UAVs) have emerged as adequate platforms to carry communications nodes, including Wi-Fi Access Points and cellular Base Stations. This has led to the concept of flying networks composed of UAVs as a flexible and agile solution to provide on-demand wireless connectivity anytime, anywhere. However, state of the art works have been focused on optimizing the placement of the access network providing connectivity to ground users, overlooking the backhaul network design. In order to improve the overall Quality of Service (QoS) offered to ground users, the placement of Flyin…
New Mexico Tech（新墨西哥理工学院）；Amir Kabir University of Technology（阿米尔·卡比尔理工大学）；Utah Valley university（犹他谷大学）
Temporary high traffic requests in cellular networks is a challenging problem to address. Recent advances in Unmanned Aerial Vehicles applied to cover these types of traffics. UAV -Mounted Mobile Base Stations placement is a challenging problem to achieve high performance. Different approaches have been proposed; however, user required traffic is not considered in UAV placement. We propose a new feature to apply to K-means clustering to find the optimum clusters. User required traffic is defined as a new feature to assign users to the UAVs. Our simulation results show that UAVs could be placed…
With the explosive increment of computation requirements, the multi-access edge computing (MEC) paradigm appears as an effective mechanism. Besides, as for the Internet of Things (IoT) in disasters or remote areas requiring MEC services, unmanned aerial vehicles (UAVs) and high altitude platforms (HAPs) are available to provide aerial computing services for these IoT devices. In this paper, we develop the hierarchical aerial computing framework composed of HAPs and UAVs, to provide MEC services for various IoT applications. In particular, the problem is formulated to maximize the total IoT dat…
Unmanned Aerial Vehicles (UAVs) have been extensively utilized to provide wireless connectivity in rural and under-developed areas, enhance network capacity and provide support for peaks or unexpected surges in user demand, mainly due to their fast deployment, cost-efficiency and superior communication performance resulting from Line of Sight (LoS)-dominated wireless channels. In order to exploit the benefits of UAVs as base stations or relays in a mobile network, a major challenge is to determine the optimal UAV placement and relocation strategy with respect to the mobility and traffic patter…
In this paper, we consider an unmanned aerial vehicle (UAV) enabled relaying system where multiple UAVs are deployed as aerial relays to support simultaneous communications from a set of source nodes to their destination nodes on the ground. An optimization problem is formulated under practical channel models to maximize the minimum achievable expected rate among all pairs of ground nodes by jointly designing UAVs' three-dimensional (3D) placement as well as the bandwidth-and-power allocation. This problem, however, is non-convex and thus difficult to solve. As such, we propose a new method, c…
In this paper, we consider an Unmanned Aerial Vehicle (UAV)-assisted cellular system which consists of multiple UAV base stations (BSs) cooperating the terrestrial BSs. In such a heterogeneous network, for cellular operators, the problem is how to determine the appropriate number, locations, and altitudes of UAV-BSs to improve the system sumrate as well as satisfy the demands of arbitrarily flash crowds on data rates. We propose a data-driven 3D placement of UAV-BSs for providing an effective placement result with a feasible computational cost. The proposed algorithm searches for the appropria…
Federal Aviation Administration (FAA) of the United States is considering Remote ID systems for unmanned aerial vehicles (UAVs). These systems act as license plates used on automobiles, but they transmit information using radio waves. To be useful, the transmissions in such systems need to reach long distances to minimize the number of ground stations to capture these transmissions. LoRaWAN is designed as a cheap long-range technology to be used for long-range communication for the Internet of Things. Several manufacturers make LoRaWAN modules, which are readily available on the market and are…
A swarm of cooperating UAVs communicating with a distant multiantenna ground station can leverage MIMO spatial multiplexing to scale the capacity. Due to the line-of-sight propagation between the swarm and the ground station, the MIMO channel is highly correlated, leading to limited multiplexing gains. In this paper, we optimize the UAV positions to attain the maximum MIMO capacity given by the single user bound. An infinite set of UAV placements that attains the capacity bound is first derived. Given an initial swarm placement, we formulate the problem of minimizing the distance traveled by t…
Several solutions have been proposed in the literature to address the Unmanned Aerial Vehicles (UAVs) collision avoidance problem. Most of these solutions consider that the ground controller system (GCS) determines the path of a UAV before starting a particular mission at hand. Furthermore, these solutions expect the occurrence of collisions based only on the GPS localization of UAVs as well as via object-detecting sensors placed on board UAVs. The sensors' sensitivity to environmental disturbances and the UAVs' influence on their accuracy impact negatively the efficiency of these solutions. I…
Agility and resilience requirements of future cellular networks may not be fully satisfied by terrestrial base stations in cases of unexpected or temporary events. A promising solution is assisting the cellular network via low-altitude unmanned aerial vehicles equipped with base stations, i.e., drone-cells. Although drone-cells provide a quick deployment opportunity as aerial base stations, efficient placement becomes one of the key issues. In addition to mobility of the drone-cells in the vertical dimension as well as the horizontal dimension, the differences between the air-to-ground and ter…
National Chiao Tung University（国立交通大学）；University of Houston（休斯顿大学）
The unmanned aerial vehicles base stations (UAV-BSs) have great potential in being widely used in many dynamic application scenarios. In those scenarios, the movements of served user equipments (UEs) are inevitable, so the UAV-BSs needs to be re-positioned dynamically for providing seamless services. In this paper, we propose a system framework consisting of UEs clustering, UAV-BS placement, UEs trajectories prediction, and UAV-BS reposition matching scheme, to serve the UEs seamlessly as well as minimize the energy cost of UAV-BSs' reposition trajectories. An Echo State Network (ESN) based al…
URLLC-Aware Proactive UAV Placement in Internet of Vehicles
New Jersey Institute of Technology（新泽西理工学院）；Maynooth University（梅努斯大学）；University of Peradeniya（佩拉德尼亚大学）；University of Oulu（奥卢大学）；Khalifa University of Science and Technology（哈利法科学技术大学）；CentraleSupélec, Université Paris-Saclay（巴黎萨克雷大学中央理工-高等电力学院）
Connectivity-Aware UAV Path Planning with Aerial Coverage Maps
Department of ECE, Hong Kong University of Science and Technology, Hong Kong（香港科技大学电子工程系）；Department of EIE, The Hong Kong Polytechnic University, Hong Kong（香港理工大学电子工程系）
Unmanned Aerial Vehicle (UAV) networks can provide a resilient communication infrastructure to enhance terrestrial networks in case of traffic spikes or disaster scenarios. However, to be able to do so, they need to be based on high-bandwidth wireless technologies for both radio access and backhaul. With this respect, the millimeter wave (mmWave) spectrum represents an enticing solution, since it provides large chunks of untapped spectrum that can enable ultra-high data-rates for aerial platforms. Aerial mmWave channels, however, experience characteristics that are significantly different from…
The communication system is a critical part of the system design for the autonomous UAV. It has to address different considerations, including efficiency, reliability and mobility of the UAV. In addition, a multi-UAV system requires a communication system to assist information sharing, task allocation and collaboration in a team of UAVs. In this paper, we review communication solutions for supporting a team of UAVs while considering an application in the power line inspection industry. We provide a review of candidate wireless communication technologies {for supporting communication in UAV app…
Unmanned aerial vehicle (UAV) swarm enabled edge computing is envisioned to be promising in the sixth generation wireless communication networks due to their wide application sensories and flexible deployment. However, most of the existing works focus on edge computing enabled by a single or a small scale UAVs, which are very different from UAV swarm-enabled edge computing. In order to facilitate the practical applications of UAV swarm-enabled edge computing, the state of the art research is presented in this article. The potential applications, architectures and implementation considerations …
In the next few years, smart farming will reach each and every nook of the world. The prospects of using unmanned aerial vehicles (UAV) for smart farming are immense. However, the cost and the ease in controlling UAVs for smart farming might play an important role for motivating farmers to use UAVs in farming. Mostly, UAVs are controlled by remote controllers using radio waves. There are several technologies such as WiFi or ZigBee that are also used for controlling UAVs. However, Smart Bluetooth (also referred to as Bluetooth Low Energy) is a wireless technology used to transfer data over shor…
Cellular-based Unmanned Aerial Vehicle (UAV) systems are a promising paradigm to provide reliable and fast Beyond Visual Line of Sight (BVLoS) communication services for UAV operations. However, such systems are facing a serious GPS spoofing threat for UAV's position. To enable safe and secure UAV navigation BVLoS, this paper proposes a cellular network assisted UAV position monitoring and anti-GPS spoofing system, where deep learning approach is used to live detect spoofed GPS positions. Specifically, the proposed system introduces a MultiLayer Perceptron (MLP) model which is trained on the s…
Unmanned aerial vehicles (UAVs) are becoming more common, and their operational range is expanding tremendously, making the security aspect of the inquiry essential. This study does a thorough assessment of the literature to determine the most common cyberattacks and the effects they have on UAV assaults on civilian targets. The STRIDE assault paradigm, the challenge they present, and the proper tools for the attack are used to categorize the cyber dangers discussed in this paper. Spoofing and denial of service assaults are the most prevalent types of UAV cyberattacks and have the best results…
Autonomy of devices is a major challenge in many Internet of Things (IoT) applications, in particular when the nodes are deployed remotely or difficult to assess places. In this paper we present an approach to provide energy to these devices by Unmanned Aerial Vehicles (UAVs). Therefore, the two major challenges, finding and charging the node are presented. We propose a model to give the energy constrained node an unlimited autonomy by taken the Wireless Power Transfer (WPT) link and battery capacity into account. Selecting the most suitable battery technology allows a reduction in battery cap…
University of Tehran（德黑兰大学）；Carleton University（卡尔顿大学）
In this paper, we use an aerial base station (aerial-BS) to enhance fairness in a dynamic environment with user mobility. The problem of optimally placing the aerial-BS is a non-deterministic polynomial-time hard (NP-hard) problem. Moreover, the network topology is subject to continuous changes due to the user mobility. These issues intensify the quest to develop an adaptive and fast algorithm for 3D placement of the aerial-BS. To this end, we propose a method based on reinforcement learning to achieve these goals. Simulation results show that our method increases fairness among users in a rea…
Unmanned aerial vehicles (UAVs), as aerial base stations, are a promising solution for providing wireless communications, thanks to their high flexibility and autonomy. Moreover, emerging services, such as extended reality, require high-capacity communications. To achieve this, millimeter wave (mmWave), and recently, terahertz bands have been considered for UAV communications. However, communication at these high frequencies requires a line-of-sight (LoS) to the terminals, which may be located in 3D space and may have extremely limited direct-line-of-view (LoV) due to blocking objects, like bu…
Unmanned aerial vehicles serving as aerial base stations (UAV-BSs) can be deployed to provide wireless connectivity to ground devices in events of increased network demand, points-of-failure in existing infrastructure, or disasters. However, it is challenging to conserve the energy of UAVs during prolonged coverage tasks, considering their limited on-board battery capacity. Reinforcement learning-based (RL) approaches have been previously used to improve energy utilization of multiple UAVs, however, a central cloud controller is assumed to have complete knowledge of the end-devices' locations,…
This paper studies the problem of spectrum shortage in an unmanned aerial vehicle (UAV) network during critical missions such as wildfire monitoring, search and rescue, and disaster monitoring. Such applications involve a high demand for high-throughput data transmissions such as real-time video-, image-, and voice- streaming where the assigned spectrum to the UAV network may not be adequate to provide the desired Quality of Service (QoS). In these scenarios, the aerial network can borrow an additional spectrum from the available terrestrial networks in the trade of a relaying service for them…
