SkyLiTE: Low-altitude UAV Networks for Providing On-Demand LTE Connectivity

 

 

SkyLiTE Deployment

 

Advances in mobile (cellular) networks have ushered in an era of abundant connectivity. However, the stationary and expensive nature of their deployment has limited their ability to provide true “ubiquitous” connectivity under the 5G vision – especially to areas where connectivity is sparing or nonexistent (e.g. rural areas), has been compromised (e.g. disasters), or demands are extreme (e.g. venues/hotspots).

The recent advances in un-manned aerial vehicle (UAVs) technology have the potential to change the landscape of wide-area wireless connectivity by bringing a new dimension – “mobility” to the cellular network infrastructure itself. While Google’s Project Loon and Facebook’s Project Aquila are examples of high-altitude, long-endurance UAV-based connectivity efforts in this direction, the telecom operators (e.g. AT&T and Verizon) have been exploring low-altitude UAV-based LTE solutions for on-demand deployments. By deploying base stations on each of the UAVs, service providers can now deploy and tear-down these cellular networks “in the sky” in an on-demand and flexible manner. This allows them to supplement static mobile networks in areas where additional connectivity is needed, or provide stand-alone connectivity in areas where existing mobile networks are either absent or compromised. Understandably, these projects are in their very early stages -- realizing this vision of deploying heavy-weight cellular networks (e.g. LTE) on light-weight, resource-constrained platforms such as UAVs, faces several formidable challenges both in design and deployment. This is complicated by the complex nature of cellular networks that involve multiple interacting components – radio access network (RAN), evolved packet core (EPC) network and backhaul transport network.

Our goal is to explore the end-to-end design of such UAV-based connectivity networks particularly in the context of low-altitude UAV networks providing LTE connectivity. As a first step in this direction, we need to understand both the challenges as well as the potential offered by these unconventional connectivity solutions. Specifically, we need to unravel the challenges that span across multiple layers (access, core network, backhaul) in an inter-twined manner as well as the richness and complexity of the design space itself. To help network practitioners navigate this complex design space towards a solution, we have architected the end-to-end design of such a system called SkyLiTE – a self-organizing network of low-altitude UAVs that aim to provide optimized LTE connectivity in a desired region.

 

 

SkyLiTE Architecture

 

Our “SkyLiTE” system is one of the first efforts to design and deploy an on-demand, un-tethered, multi-cell LTE network (on UAVs) that can self-configure itself in the sky. SkyLiTE consists of three main components - SkyRAN, SkyCore and SkyHaul that re-architect the various components (RAN, core and backhaul transport respectively) of a cellular network to make it deployable on challenging UAV platforms in highly dynamic environments. We hope the validation of SkyLiTE in real-world deployments, will help contribute to a new era of mobile networks that can fly and make connectivity both abundant and ubiquitous.

 

 SkyLiTE System

 

Check this page for updates on SkyLiTE's progress and various articles relating to its design and deployment. A short demo of some of the applications enabled by SkyLiTE can be found below.

  • "SkyLiTE: End-to-End Design of Low-altitude UAV Networks for Providing LTE Connectivity." K. Sundaresan, E. Chai, A. Chakraborty, and S. Rangarajan, NEC Technical Report, Dec 2017 (On Arxiv).
  • "SkyCore: Moving Core to the Edge for Un-tethered and Reliable UAV-based LTE Networks", M. Moradi, K. Sundaresan, E, Chai, S. Rangarajan, M. Mao, Best paper award, ACM MobiCom, Oct 2018.
  • "SkyRAN: A Self-Organizing LTE RAN in the Sky", A. Chakraborty, E. Chai, K. Sundaresan, A. Khojasptepour, S. Rangarajan, ACM CoNEXT, Dec 2018.