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IKTPLUSS-IKT og digital innovasjon

Ubiquitous Connectivity via Autonomous Airborne Networks

Alternative title: Datatilgang Overalt via Autonome Flygende Nettverk

Awarded: NOK 12.6 mill.

This project targets a set of key contributions intended to develop the technology of unmanned aerial vehicles (UAVs) such as zeppelins, balloons, and multicopters that autonomously navigate through the airspace to provide data connectivity in those locations where it is absent or unsatisfactory. While households in developed countries receive skyrocketing data rates through optical fibers and smartphones step into the 5G era, roughly one half of the world's population cannot connect to the internet. Even beyond developing economies, bringing data connectivity to areas where it cannot currently reach would drastically benefit applications such as the internet-of-things, smart agriculture/forestry, wildfire suppression, search-and-rescue missions, paramedical interventions, and emergency response handling to name a few. To this end, the UAVs in the targeted technology are equipped with a communication module that connects to the ground users on one side and to the cellular terrestrial infrastructure on the other side. The user information may even be relayed through multiple UAVs before reaching its destination. For this technology to be viable, the UAVs must be able to navigate without human supervision to locations with favorable propagation conditions, that is, where the signals that they receive from and transmit to the ground users and cellular infrastructure are not significantly blocked by obstacles such as buildings or mountains. The key approach in this project is to construct "radio maps" that describe the propagation conditions in a certain region. Using these maps, the UAVs rely on artificial intelligence algorithms to determine the appropriate locations and can even adapt to changes in the user positions and connectivity requirements as well as to coordinate with other UAVs. Our results so far demonstrate that artificial deep neural networks can be used to learn propagation patterns from data sets of past measurements and efficiently construct radio maps from a small number of measurements collected by the UAVs. We have also developed a scheme where the aerial base stations leverage radio map information to find suitable positions for communication with the ground users.

While households in developed countries receive skyrocketing data rates through optical fibers and smartphones step into the 5G era, roughly one half of the world’s population cannot connect to the internet. Even beyond developing economies, the entire humanity would benefit from the capability of bringing data connectivity to areas where it cannot currently reach since it would drastically benefit applications such as the internet-of-things, smart agriculture/forestry, wildfire suppression, search-and-rescue missions, paramedical interventions, and emergency response handling to name a few. To address this need for ubiquitous connectivity, the 3GPP consortium, which develops the 5G standards, is regulating the integration between satellites and communication unmanned aerial vehicles (C-UAVs) to combine the benefits of the former, which provide low data rates in large areas, and the latter, which provide high data rates in smaller areas. C-UAVs are balloons, zeppelins, or multicopters with an onboard relay or base station that provides internet access to ground users by connecting to satellites, terrestrial base stations, or other C-UAVs; see Fig. 1. For this technology to become a reality, key technological developments are still required. Particularly, existing systems are oblivious to the propagation conditions of each location. Instead, they rely on statistical characterizations of average scenarios that fail to capture the specifics of each propagation situation. This proposal targets a comprehensive set of algorithms and procedures for C-UAV systems to govern navigation and communication where the decision-making is aware of the radiofrequency (RF) environment and the user conditions. More specifically maps of the propagation channel are constructed based on measurements collected by ground users, C-UAVs, and (possibly) satellites. These maps are then utilized by C-UAVs to navigate and place themselves at positions with favorable propagation conditions.

Publications from Cristin

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Funding scheme:

IKTPLUSS-IKT og digital innovasjon