Ubiquitous Connectivity via Autonomous Airborne Networks

This project deals with the development of 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 and smartphones in developed countries receive skyrocketing data rates through optical fibers and 5G communications, 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 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 comprise a substantial set of contributions at three levels: fundamentals, algorithmic, and empirical. At the fundamental level, we were the first group worldwide to analyze the radio map estimation problem from an abstract mathematical perspective and to derive performance bounds for simple estimators. This allows one to know beforehand when a radio map estimate will be good or not. At the algorithmic level, we developed algorithms of multiple kinds, mainly algorithms to plan the trajectory of unmanned aerial vehicles (UAVs) to efficiently collect measurements for radio map estimation (spectrum surveying), and algorithms to determine the position of aerial base stations and relays using radio maps. Finally, at the empirical level, we were also the first group worldwide to carry out an empirical study of radio map estimation and to construct a system that allows the fast collection of measurement data for radio map estimation using UAVs. We will soon publish a large dataset which we expect to be used by the entire community.

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.