Development of Air-to-Ground Connectivity for 5G UTM Networks
Lead Research Organisation:
CRANFIELD UNIVERSITY
Department Name: Sch of Aerospace, Transport & Manufact
Abstract
The unmanned aerial vehicles (UAVs) are new types of user equipment connected to cellular networks with promising revenue through additional new subscribers and use cases, especially for aviation sector. In addition, UAVs are accepted as an extension to base stations by boosting coverage, spectral efficiency and user quality of experience.
In this context, the main aim of this project is to provide high quality of data link and smooth UAVs connectivity into cellular network infrastructure. The UAVs allow rapid deployment of a multi-hop communication backbone in challenging environments with applications for public safety, delivery and monitoring. Therefore, Unmanned aerial vehicles (UAVs) can be used as complementary infrastructure to provide wireless services for the ground users or they may require wireless connectivity from the ground for a safe and reliable operation.
This PhD project aims to study several UAV use-cases covering 5G core networks and to validate UAV/UTM connectivity KPIs for supporting such challenging. The project will drive UAV and 5G networks to a win-win position, on one hand by showing that 5G is able to guarantee UAV vertical KPIs, and on the other hand by demonstrating that 5G can support challenging use-cases that put pressure on network resources. To achieve that we will look to study of where 5G can add value to improve the existing UAV connectivity.
In this context, the main aim of this project is to provide high quality of data link and smooth UAVs connectivity into cellular network infrastructure. The UAVs allow rapid deployment of a multi-hop communication backbone in challenging environments with applications for public safety, delivery and monitoring. Therefore, Unmanned aerial vehicles (UAVs) can be used as complementary infrastructure to provide wireless services for the ground users or they may require wireless connectivity from the ground for a safe and reliable operation.
This PhD project aims to study several UAV use-cases covering 5G core networks and to validate UAV/UTM connectivity KPIs for supporting such challenging. The project will drive UAV and 5G networks to a win-win position, on one hand by showing that 5G is able to guarantee UAV vertical KPIs, and on the other hand by demonstrating that 5G can support challenging use-cases that put pressure on network resources. To achieve that we will look to study of where 5G can add value to improve the existing UAV connectivity.
Organisations
People |
ORCID iD |
| Saba Al-Rubaye (Primary Supervisor) | |
| Anirudh Warrier (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/T518104/1 | 01/10/2020 | 30/09/2025 | |||
| 2459795 | Studentship | EP/T518104/1 | 01/10/2020 | 30/09/2023 | Anirudh Warrier |
| Description | Unmanned Aerial Vehicles (UAVs) or drones are expected to enable a wide range of applications including, delivery, military, agriculture, photography etc. This involves UAVs operating on beyond visual line of sight (BVLoS) range, meaning that UAVs still need to be tracked and communicated with even if they are visible to the operator. This can be enabled by integrating it to the fifth-generation (5G) networks. Cellular networks like 5G are available ubiquitously, therefore is a great solution to enable BVLoS operations. However, this integration comes with certain challenges. Developing solutions to these challenges are the main objectives of this project. In particular novel algorithms for seamless handover in both rural and urban areas and interference mitigation were developed. For the former, we proposed an entropy weighted decision making algorithm in the urban areas and graph theory based solution for rural areas. For the latter, a deep Q learning algorithm was developed |
| Exploitation Route | For future researchers, there could be additional challenges to be resolved especially on the regulatory side of things specifically to deal with UAV safety and AI integration. Following which, the implementation and deployment of the solutions proposed in this project. |
| Sectors | Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Electronics |
| URL | https://ieeexplore.ieee.org/document/9925817 |
| Description | The unmanned aerial vehicle (UAVs) service-provider sector is growing faster than any other. Companies in that sector are particularly interested in the evolution of 5G because it can boost their quality of service and innovation. The work done in this PhD aims to integrate UAVs with 5G and create an ecosystem of 5G-connected UAVs. Such an integration will enable UAVs perform functions such as delivery of medical supplies and packages, which in turn has a huge impact on the economy. As UAVs can be used for agricultural, medical, monitoring and disaster relief it would need to overcome the challenges it faces in maintaining uninterrupted connectivity. This project proposes solutions to such problems as mobility and interference to enable UAVs within 5G networks to impact the society positively. 5G connected UAVs will also affect the public policies, as UAVs sharing the airspace with aircrafts or other aerial vehicles may create potential issues. Therefore, there is a need to develop new policies and regulations that can ensure the safety and reliability of UAVs. In the course of this PhD, the developed solutions, would require the creation of new frameworks and policies, in particular with regard to machine learning and artificial intelligence solutions, that yet do not have regulatory policies. Thus, this project, that aims at resolving the challenges of UAV-5G integration will create a huge and positive impact on the economy, society and public policies of a society or a nation. |
| First Year Of Impact | 2021 |
| Sector | Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Electronics |
| Impact Types | Societal,Economic,Policy & public services |