Wireless communication systems that include unmanned aerial vehicles promise to provide cost-effective wireless connectivity for devices without infrastructure coverage. Compared to terrestrial communications or those based on high-altitude platforms, on-demand wireless systems with low-altitude UAVs are in general faster to deploy, more flexibly reconfigured, and likely to have better communication channels due to the presence of short-range line-of-sight links. However, the utilization of highly mobile and energy-constrained UAVs for wireless communications also introduces many new challenges. In this article, we provide an overview of UAV-aided wireless communications, by introducing the basic networking architecture and main channel characteristics, highlighting the key design considerations as well as the new opportunities to be exploited.

Wireless communications with unmanned aerial vehicles: opportunities and challenges

Unmanned aerial vehicles (UAVs) have enormous potential in the public and civil domains. These are particularly useful in applications, where human lives would otherwise be endangered. Multi-UAV systems can collaboratively complete missions more efficiently and economically as compared to single UAV systems. However, there are many issues to be resolved before effective use of UAVs can be made to provide stable and reliable context-specific networks. Much of the work carried out in the areas of mobile ad hoc networks (MANETs), and vehicular ad hoc networks (VANETs) does not address the unique characteristics of the UAV networks. UAV networks may vary from slow dynamic to dynamic and have intermittent links and fluid topology. While it is believed that ad hoc mesh network would be most suitable for UAV networks yet the architecture of multi-UAV networks has been an understudied area. Software defined networking (SDN) could facilitate flexible deployment and management of new services and help reduce cost, increase security and availability in networks. Routing demands of UAV networks go beyond the needs of MANETS and VANETS. Protocols are required that would adapt to high mobility, dynamic topology, intermittent links, power constraints, and changing link quality. UAVs may fail and the network may get partitioned making delay and disruption tolerance an important design consideration. Limited life of the node and dynamicity of the network lead to the requirement of seamless handovers, where researchers are looking at the work done in the areas of MANETs and VANETs, but the jury is still out. As energy supply on UAVs is limited, protocols in various layers should contribute toward greening of the network. This paper surveys the work done toward all of these outstanding issues, relating to this new class of networks, so as to spur further research in these areas.

Survey of Important Issues in UAV Communication Networks

The use of flying platforms such as unmanned aerial vehicles (UAVs), popularly known as drones, is rapidly growing. In particular, with their inherent attributes such as mobility, flexibility, and adaptive altitude, UAVs admit several key potential applications in wireless systems. On the one hand, UAVs can be used as aerial base stations to enhance coverage, capacity, reliability, and energy efficiency of wireless networks. On the other hand, UAVs can operate as flying mobile terminals within a cellular network. Such cellular-connected UAVs can enable several applications ranging from real-time video streaming to item delivery. In this paper, a comprehensive tutorial on the potential benefits and applications of UAVs in wireless communications is presented. Moreover, the important challenges and the fundamental tradeoffs in UAV-enabled wireless networks are thoroughly investigated. In particular, the key UAV challenges such as 3D deployment, performance analysis, channel modeling, and energy efficiency are explored along with representative results. Then, open problems and potential research directions pertaining to UAV communications are introduced. Finally, various analytical frameworks and mathematical tools, such as optimization theory, machine learning, stochastic geometry, transport theory, and game theory are described. The use of such tools for addressing unique UAV problems is also presented. In a nutshell, this tutorial provides key guidelines on how to analyze, optimize, and design UAV-based wireless communication systems.

/pdf/a-tutorial-on-uavs-for-wireless-networks-applications-2heqa4nlgr.pdf

A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems

In this paper, the deployment of an unmanned aerial vehicle (UAV) as a flying base station used to provide the fly wireless communications to a given geographical area is analyzed. In particular, the coexistence between the UAV, that is transmitting data in the downlink, and an underlaid device-to-device (D2D) communication network is considered. For this model, a tractable analytical framework for the coverage and rate analysis is derived. Two scenarios are considered: a static UAV and a mobile UAV. In the first scenario, the average coverage probability and the system sum-rate for the users in the area are derived as a function of the UAV altitude and the number of D2D users. In the second scenario, using the disk covering problem, the minimum number of stop points that the UAV needs to visit in order to completely cover the area is computed. Furthermore, considering multiple retransmissions for the UAV and D2D users, the overall outage probability of the D2D users is derived. Simulation and analytical results show that, depending on the density of D2D users, the optimal values for the UAV altitude, which lead to the maximum system sum-rate and coverage probability, exist. Moreover, our results also show that, by enabling the UAV to intelligently move over the target area, the total required transmit power of UAV while covering the entire area, can be minimized. Finally, in order to provide full coverage for the area of interest, the tradeoff between the coverage and delay, in terms of the number of stop points, is discussed.

/pdf/unmanned-aerial-vehicle-with-underlaid-device-to-device-1jwhf0rdfl.pdf

Unmanned Aerial Vehicle With Underlaid Device-to-Device Communications: Performance and Tradeoffs

The use of flying platforms such as unmanned aerial vehicles (UAVs), popularly known as drones, is rapidly growing. In particular, with their inherent attributes such as mobility, flexibility, and adaptive altitude, UAVs admit several key potential applications in wireless systems. On the one hand, UAVs can be used as aerial base stations to enhance coverage, capacity, reliability, and energy efficiency of wireless networks. On the other hand, UAVs can operate as flying mobile terminals within a cellular network. Such cellular-connected UAVs can enable several applications ranging from real-time video streaming to item delivery. In this paper, a comprehensive tutorial on the potential benefits and applications of UAVs in wireless communications is presented. Moreover, the important challenges and the fundamental tradeoffs in UAV-enabled wireless networks are thoroughly investigated. In particular, the key UAV challenges such as three-dimensional deployment, performance analysis, channel modeling, and energy efficiency are explored along with representative results. Then, open problems and potential research directions pertaining to UAV communications are introduced. Finally, various analytical frameworks and mathematical tools such as optimization theory, machine learning, stochastic geometry, transport theory, and game theory are described. The use of such tools for addressing unique UAV problems is also presented. In a nutshell, this tutorial provides key guidelines on how to analyze, optimize, and design UAV-based wireless communication systems.

IntroductionAs a result of advances in communication, computation, sensor and energy storage technologies, as well as carbon fiber-reinforced plastic materials, micro unmanned aerial vehicles (UAV) are available at affordable prices. On this basis many new application areas, such as the in-depth reconnaissance and surveillance of major incidents, will be possible. Uncontrolled emissions of liquid or gaseous contaminants in cases of volcanic eruptions, large fires, industrial incidents, or terrorist attacks can be analyzed by utilizing UAV (Figure 1). Hence, the use of cognitive Unmanned Aerial Systems (UAS) for distributing mobile sensors in incident areas is in general a significant value added for remote sensing, reconnaissance, surveillance, and communication purposes.1Figure 1: Deployment Scenario: Chemical Plume Detection with an Autonomous Micro UAV Mesh Network.In the near future police departments, fire brigades and other homeland security organizations will have access to medium- and small-size UAV and will integrate them in their work flow. The use of non-military frequencies and civil communication technologies gains in importance for purposes of safety and security missions, since the frequency pool is limited and nearly exhausted. In particular, regionally organized public authorities and small rescue organizations like fire brigades often have insufficient access to frequencies and expensive communication equipment. Thus, using civil mobile communication systems is often the only effective workaround for homeland security organizations.This is also one of the major issues for wireless communication in the area of unmanned aerial systems (UAS). Besides flight regulation, wireless communication is an important aspect of UAS as telemetry information (navigation, control, guidance) and sensor data usually have to be transmitted to a mission control center (MCC) in nearly real-time. Today, there is no viable alternative for this type of transmission besides using civil mobile communication networks. Unfortunately, there is no foreseeable solution in terms of frequency assignment for UAS. For efficient sensor coverage of large industrial and incident areas, fast and flexible strategies for collecting sensor data through an autonomous, reliably connected UAV need to be developed. In this article we focus on the civilian concepts of operations (CONOPS) for UAV, in particular for small-scale UAV. Viable concepts on the system level for leveraging public wireless communication networks for UAV-based cognitive remote sensing are presented with respect to both existing constraints and user requirements.The article is structured as follows: we first present the current state of the art and related research activities in the area of UAS communication. Civilian concepts of operations (CONOPS) for purposes of homeland security are discussed in the next section. Subsequent sections address the requirements, concepts and solutions for Air-to-Air (A2A), Air-to-Ground (A2G), and UAS-backend communication. On this basis we then show a methodology for agent-based UAV-mobility for areas with insufficient communication. The article ends suggestions for future research.Related Work and ProjectsSeveral research investigations have been done in the area of UAS. However, UAS communication aspects mostly address proprietary communication systems and usually do not consider public wireless infrastructures since these systems have been mostly deployed by military organizations in the past. Hence, we identify a demand for more in-depth contributions for UAS communication by means of public wireless networks.Tiwari and others have studied the placement planning problem of an airborne network.2 They offer a toolbox to optimize the ground coverage while maintaining a certain degree of reliability and connectivity. By introducing practical scenarios for deployment, the interaction between communication design and mobility planning is shown. …

/pdf/using-public-network-infrastructures-for-uav-remote-sensing-45uf0lfvog.pdf

Using Public Network Infrastructures for UAV Remote Sensing in Civilian Security Operations

Ad-hoc aerial sensor networks leveraging MUAVs (Micro Unmanned Aerial Vehicles) are ideally suited to cost-efficiently explore unknown or hostile environments for example in case of incidents producing harmful gases or radiation In this manuscript we present results on the investigations of communication-aware steering algorithms for cooperative MUAV swarms The mission objective is to achieve a maximum spatial exploration efficiency with the simultaneous ability to self-optimize the communication links by exploiting controlled mobility While our previous work has mainly considered the performance of the Air-to-Air mesh network, in this paper we focus on the Air-to-Ground-link connectivity control To achieve appropriate communication links to a central sensor data sink even while exploring larger search areas, an agent-based role management strategy is used to provide suitable multi-hop connectivity The novel algorithms are investigated for static as well as dynamically changing environments Key results include a detailed realistic aerial channel characterization and network dimensioning analysis considering numbers of MUAVs and density of ground stations vs exploration speed and sensor data latency

Role-Based Connectivity Management with Realistic Air-to-Ground Channels for Cooperative UAVs

For clarification, containment and combat of large danger areas, fast and flexible survey of potentially contaminated areas is an emerging challenge. In this paper we present a project that focuses on incidents, that are caused by uncontrolled emissions of liquid or gaseous contaminants (e.g. explosive or toxic gases or liquids, biological, chemical or nuclear weapons). Instead of sending specially equipped forces with expensive transport and measurement devices into the contaminated area, our proposed system makes use of an autonomous, wireless connected swarm of Micro Unmanned Aerial Vehicles (MUAV), often simply known as drones, that are featured with lightweight mobile sensor systems. In this paper we will be particularly focusing on the complex communication system, which on the one hand has to organize the on-board-communication between the control systems of the MUAV and the sensors and on the other hand has to establish wireless connections to the mission control center on the ground as well as to neighboring MUAVs in the air via a mesh network.

AirShield: A system-of-systems MUAV remote sensing architecture for disaster response

Unmanned Aerial Vehicles (UAVs) gained a lot popularity during the last years and are used in many applications ranging from reconnaissance over disaster recovery to remote sensing [1][2]. In most applications some sort of communication link is needed to transmit telemetry and payload data. Especially for homeland security and civil operations the realization is sometimes very demanding due to missing radio frequencies. In order to overcome this constraint we investigate the usability of existing cellular networks. Considering these UAVs to communicate by means of cellular networks for establishing reliable air-to-ground links, claims an analysis and evaluation of the cellular channel characteristics in the low altitude operational area. In this paper we present a coverage analysis for cellular networks for altitudes up to 500m based on aerial RSSI measurements.

Coverage evaluation of wireless networks for Unmanned Aerial Systems

For efficient sensor coverage of large industrial and incident areas, fast and flexible strategies for collecting sensor data through an autonomous, wirelessly connected swarm of (Micro) Unmanned Aerial Vehicles (MUAVs) are still an emerging challenge. Deploying multiple MUAVs which stably carry sensing equipment in hostile environments yields cost efficiency and reducing the risk to human life. The use of an aerial ad hoc sensor network based on MUAV agents promises more timely and accurate information by fusing measurements from different types of sensors. In this paper, we examine agent-based mobility algorithms that target high spatial coverage distribution, high total coverage, and high-quality communication links. For these key figures, the performance of the different novel mobility algorithms is evaluated. We particularly focus on channel aware mobility and on self-organizing mesh topologies of MUAV-based sensor swarms with respect to communication constraints.

Kai Daniel

Papers

Using Public Network Infrastructures for UAV Remote Sensing in Civilian Security Operations

Role-Based Connectivity Management with Realistic Air-to-Ground Channels for Cooperative UAVs

AirShield: A system-of-systems MUAV remote sensing architecture for disaster response

Coverage evaluation of wireless networks for Unmanned Aerial Systems

Cognitive Agent Mobility for Aerial Sensor Networks