Hybrid LoRa-IEEE 802.11s Opportunistic Mesh Networking for Flexible UAV Swarming

Unmanned Aerial Vehicles (UAVs) and small drones are nowadays being widely used in heterogeneous use cases: aerial photography, precise agriculture, inspections, environmental data collection, search-and-rescue operations, surveillance applications, and more. When designing UAV swarm-based applications, a key "ingredient" to make them effective is the communication system (possible involving multiple protocols) shared by flying drones and terrestrial base stations. When compared to ground communication systems for swarms of terrestrial vehicles, one of the main advantages of UAV-based communications is the presence of direct Line-of-Sight (LOS) links between flying UAVs operating at an altitude of tens of meters, often ensuring direct visibility among themselves and even with some ground Base Transceiver Stations (BTSs). Therefore, the adoption of proper networking strategies for UAV swarms allows users to exchange data at distances (significantly) longer than in ground applications. In this paper, we propose a hybrid communication architecture for UAV swarms, leveraging heterogeneous radio mesh networking based on long-range communication protocols—such as LoRa and LoRaWAN—and IEEE 802.11s protocols. We then discuss its strengths, constraints, viable implementation, and relevant reference use cases

Low-Cost UAV Swarm for Real-Time Object Detection Applications

With unmanned aerial vehicles (UAVs), also known as drones, becoming readily available and affordable, applications for these devices have grown immensely. One type of application is the use of drones to fly over large areas and detect desired entities. For example, a swarm of drones could detect marine creatures near the surface of the ocean and provide users the location and type of animal found. However, even with the reduction in cost of drone technology, such applications result costly due to the use of custom hardware with built-in advanced capabilities. Therefore, the focus of this thesis is to compile an easily customizable, low-cost drone design with the necessary hardware for autonomous behavior, swarm coordination, and on-board object detection capabilities. Additionally, this thesis outlines the necessary network architecture to handle the interconnection and bandwidth requirements of the drone swarm. The drone on-board system uses a PixHawk 4 flight controller to handle flight mechanics, a Raspberry Pi 4 as a companion computer for general-purpose computing power, and a NVIDIA Jetson Nano Developer Kit to perform object detection in real-time. The implemented network follows the 802.11s standard for multi-hop communications with the HWMP routing protocol. This topology allows drones to forward packets through the network, significantly extending the flight range of the swarm. Our experiments show that the selected hardware and implemented network can provide direct point-to-point communications at a range of up to 1000 feet, with extended range possible through message forwarding. The network also provides sufficient bandwidth for bandwidth intensive data such as live video streams. With an expected flight time of about 17 minutes, the proposed design offers a low-cost drone swarm solution for mid-range aerial surveillance applications

Medium Access Control and Routing Protocols Design for 5G

In future wireless systems, such as 5G and beyond, the current dominating human-centric communication systems will be complemented by a tremendous increase in the number of smart devices, equipped with radio devices, possibly sensors, and uniquely addressable. This will result in explosion of wireless traffic volume, and consequently exponential growth in demand of radio spectrum. There are different engineering techniques for resolving the cost and scarcity of radio spectrum such as coexistence of diverse devices on the same pool of radio resources, spectrum aggregations, adoption of mmWave bands with huge spectrum, etc. The aim of this thesis is to investigate Medium Access Control (MAC) and routing protocols for 5G and beyond radio networks. Two scenarios are addressed: heterogeneous scenario where scheduled and uncoordinated users coexist, and a scenario where drones are used for monitoring a given area. In the heterogeneous scenario scheduled users are synchronised with the Base Station (BS) and rely on centralised resource scheduler for assignment of time slots, while the uncoordinated users are asynchronous with each other and the BS and rely unslotted Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) for channel access. First, we address a single-hop network with advanced scheduling algorithm design and packet length adaptation schemes design. Second, we address a multi-hop network with novel routing protocol for enhancing performance of the scheduled users in terms of throughput, and coexistence of all network users. In the drone-based scenario, new routing protocols are designed to address the problems of Wireless Mesh Networks with monitoring drones. In particular, a novel optimised Hybrid Wireless Mesh Protocol (O-HWMP) for a quick and efficient discovery of paths is designed, and a capacity achieving routing and scheduling algorithm, called backpressure, investigated. To improve on the long-end-to-end delays of classical backpressure, a modified backpressure algorithm is proposed and evaluated

Customized Wireless Mesh Routing Metric for Swarm of Drones Applications

With the proliferation of drones applications, there is an increasing need for handling their numerous challenges. One of such challenges arises when a swarm-of-drones is deployed to accomplish a specific task which requires coordination and communication. While this swarm-of-drones is essentially a special form of mobile ad hoc networks (MANETs) which has been studied for many years, there are still some unique requirements of drone applications that necessitates re-visiting MANET approaches. These challenges stem from 3-D environments the drones are deployed in, and their specific way of mobility which adds to the wireless link management challenges. In this thesis, we consider the existing 802.11s wireless mesh standard and adopt its routing capabilities for swarm-of-drones. Specifically, we propose two link quality routing metrics called SrFTime and CRP metrics as an improvement to the 802.11s default Airtime routing metric, to enable better network throughput for drone applications. SrFTime improve network performance of stationary and mobile Wireless Mesh Networks, while CRP is designed to fit the link characteristics of drones and enable more efficient routes from these to their gateway. The evaluations in the actual 802.11s standard indicate that our proposed metrics outperforms the existing one consistently under various conditions

Implementation of a Wireless Mesh Network of Ultra Light MAVs with Dynamic Routing

This paper describes the implementation and characterisation of a mobile ad-hoc network (MANET) of ultra-light intelligent flying robots. The flying nature of the network makes it suitable to collect or disseminate content in urban areas or challenging terrain, where line-of-sight connection between the Micro Air Vehicles (MAVs) allows for more efficient communication. Dynamic routing in the network enables the nodes to intelligently establish multi-hop routes to extend the communication range or to overcome obstacles. The presented MANET relies on the IEEE 802.11n WiFi standard for data communications and uses the OLSR routing protocol. Routing decisions based on dynamic link quality measurements allow the network to cope with the fast variability of the wireless channel and the high mobility of the MAVs. The implementation of such a system calls for the integration of advanced communication and control technologies in a very restrictive platform, be it in terms of weight, power consumption or availability of suitable off-the-shelf hardware. A detailed description of the system design is presented, and its performance is characterised based on in-flight network measurements. To the best of our knowledge, this is the first report of OLSR successfully tested in a MANET with such fast dynamics. We verify the trade-off between achievable throughput and the number of hops, and we report on the sensitivity of communication performance and routing behaviour to MAV orientation and flight path. Mitigation of such dependencies and improvements to the routing algorithm are discussed along with future research directions

Assessing the Performance of a Particle Swarm Optimization Mobility Algorithm in a Hybrid Wi-Fi/LoRa Flying Ad Hoc Network

Research on Flying Ad-Hoc Networks (FANETs) has increased due to the availability of Unmanned Aerial Vehicles (UAVs) and the electronic components that control and connect them. Many applications, such as 3D mapping, construction inspection, or emergency response operations could benefit from an application and adaptation of swarm intelligence-based deployments of multiple UAVs. Such groups of cooperating UAVs, through the use of local rules, could be seen as network nodes establishing an ad-hoc network for communication purposes. One FANET application is to provide communication coverage over an area where communication infrastructure is unavailable. A crucial part of a FANET implementation is computing the optimal position of UAVs to provide connectivity with ground nodes while maximizing geographic span. To achieve optimal positioning of FANET nodes, an adaptation of the Particle Swarm Optimization (PSO) algorithm is proposed. A 3D mobility model is defined by adapting the original PSO algorithm and combining it with a fixed-trajectory initial flight. A Long Range (LoRa) mesh network is used for air-to-air communication, while a Wi-Fi network provides air-to-ground communication to several ground nodes with unknown positions. The optimization problem has two objectives: maximizing coverage to ground nodes and maintaining an end-to-end communication path to a control station, through the UAV mesh. The results show that the hybrid mobility approach performs similarly to the fixed trajectory flight regarding coverage, and outperforms fixed trajectory and PSO-only algorithms in both path maintenance and overall network efficiency, while using fewer UAVs

Connecting Disjoint Nodes Through a UAV-Based Wireless Network for Bridging Communication Using IEEE 802.11 Protocols

Cooperative aerial wireless networks composed of small unmanned aerial vehicles(UAVs) are easy and fast to deploy and provide on the fly communication facilities in situations where part of the communication infrastructure is destroyed and the survivors need to be rescued on emergency basis. In this article, we worked on such a cooperative aerial UAV-based wireless network to connect the two participating stations. The proposed method provides on the fly communication facilities to connect the two ground stations through a wireless access point (AP) mounted on a UAV using the IEEE 802.11a/b/g/n. We conducted our experiments both indoor and outdoor to investigate the performance of IEEE 802.11 protocol stack including a/b/g/n. We envisioned two different cases: line of sight (LoS) and non-line of sight (NLoS). In LoS, we consider three different scenarios with respect to UAV altitude and performed the experiments at different altitudes to measure the performance and applicability of the proposed system in catastrophic situations and healthcare applications. Similarly, for NLoS, we performed a single set of experiments in an indoor environment. Based on our observations from the experiments, 802.11n at 2.4 GHz outperforms the other IEEE protocols in terms of data rate followed by 802.11n at 5 GHz band. We also concluded that 802.11n is the more suitable protocol that can be practiced in disastrous situations such as rescue operations and healthcare applications

De l'évaluation des performances Wi-Fi à la mobilité contrôlée pour les réseaux de drones

Mobility in telecommunication networks is often seen as a hassle that needs to be dealt with: a mobile wireless device has to adapt is trans-mission parameters in order to remain connected to its counterpart(s),as the channel evolves with the device’s movements. Drones, which are unmanned aerial vehicles in the context of this thesis, are no exception.Because of their freedom of movement, their three-dimensional mobility in numerous and varied environments, their limited payload and their energy constraints, and because of the wide range of their real-world applications, drones represent new exciting study objects whose mobility is a challenge. Yet, mobility can also be a chance for drone networks,especially when we can control it. In this thesis, we explore how con-trolled mobility can be used to increase the performance of a drone network, with a focus on IEEE 802.11 networks and small multi-rotor drones. We first describe how mobility is dealt with in 802.11 networks,that is to say using rate adaptation mechanisms, and reverse engineer the rate adaptation algorithm used in the Wi-Fi chipset of the Intel Aero Drone. The study of this rate adaptation algorithm, both experimental and through simulation, through its implementation in the network simulator NS-3, allows its comparison against other well-known algorithms.This highlights how big the impact of such algorithms are for drone networks, with regard to their mobility, and how different the resulting behaviors of each node can be. Therefore, a controlled mobility solution aiming to improve network performances cannot assume much about the behavior of the rate adaptation algorithms. In addition to that, drone applications are diverse, and imposing mobility constraints without crippling a complete pan of these applications is difficult. We therefore propose a controlled mobility solution which leverages the antenna radiation pattern of the drones. This algorithm is evaluated thanks to a customized simulation framework for antenna and drone simulation,based on NS-3. This solution, which works with any rate adaptation algorithm, is distributed, and do not require a global coordination that would be costly. It also does not require a full and complete control of the drone mobility as existing controlled mobility solutions require, which makes this solution compatible with various applications.La mobilité dans les réseaux de télécommunications est souvent considérée comme un problème qu'il faut résoudre : un appareil mobile sans fil doit adapter ses paramètres de transmission afin de rester connecté à son ou ses homologues, car le canal évolue avec les mouvements de l'appareil. Les drones, qui sont des véhicules aériens sans pilote, ne font pas exception. En raison de leur grande liberté de mouvements, de leur mobilité tridimensionnelle, et ce dans des environnements aussi nombreux que variés, de leur charge utile limitée et de leurs contraintes énergétiques, et en raison du large éventail de leurs applications dans le monde réel, les drones représentent de nouveaux objets d'étude passionnants dont la mobilité est un défi. Pourtant, la mobilité peut aussi être une chance pour les réseaux de drones, surtout lorsque nous pouvons la contrôler. Dans cette thèse, nous explorons comment la mobilité contrôlée peut être utilisée pour augmenter les performances d'un réseau de drones, en mettant l'accent sur les réseaux IEEE 802.11 et les petits drones multi-rotor. Nous décrivons d'abord comment la mobilité est traitée dans les réseaux 802.11, c'est-à-dire en utilisant des mécanismes d'adaptation de débit, puis nous effectuons l'ingénierie inverse de l'algorithme d'adaptation de débit utilisé dans le chipset Wi-Fi du drone Intel Aero. L'étude de cet algorithme d'adaptation de débit, de manière à la fois expérimentale et par simulation, grâce à son implémentation dans le simulateur de réseau NS-3, permet de le comparer à d'autres algorithmes bien connus. Cette étude met en évidence l'importance de ces algorithmes pour les réseaux de drones, en lien avec leur mobilité, et la différence de comportement de chaque nœud en résultant. Par conséquent, une solution de mobilité contrôlée visant à améliorer les performances des réseaux ne peut pas supposer beaucoup du comportement des algorithmes d'adaptation de débits. En outre, les applications des réseaux de drones sont diverses, et il est difficile d'imposer des contraintes de mobilité sans devenir incompatible avec un pan complet d'applications. Nous proposons donc une solution de mobilité contrôlée qui exploite le diagramme de rayonnement de l'antenne des drones. Cet algorithme est évalué grâce à outil de simulation développé pour l'occasion, permettant la simulation d'antennes et de drones, basé sur NS-3. Cette solution, qui fonctionne avec n'importe quel algorithme d'adaptation de débit, est distribuée, et ne nécessite aucune coordination globale ou communication spécifique qui pourrait s'avérer coûteuses. Elle ne nécessite pas non plus un contrôle complet de la mobilité du drone comme le requièrent les solutions de mobilité contrôlée existantes, ce qui rend cette solution compatible avec diverses applications