Elena Simona Lohan*, Mike Koivisto*, Olga Galinina*, Sergey Andreev*, Antti Tölli†, Giuseppe Destino†, Mário Costa‡, Kari Leppänen‡, Evgeny Kucheryavy*, and Mikko Valkama*
* Tampere University of Technology, Finland
† University of Oulu, Finland
‡ Huawei Technologies, Finland
The future of industrial applications is shaped by intelligent moving IoT devices, such as flying drones, advanced factory robots, and connected vehicles, which may operate (semi-)autonomously. In these challenging scenarios, dynamic radio connectivity at high frequencies, augmented with timely positioning-related information, becomes instrumental to improve communication performance and facilitate efficient computation offloading. Our work reviews the main research challenges and reveals open implementation gaps in Industrial IoT (IIoT) applications relying on location awareness and multi-connectivity in super high (SHF) and extremely high (EHF) frequency bands. It further conducts a rigorous numerical investigation with our hybrid evaluation methodology to confirm the importance of device localization in the emerging IIoT systems. We focus on positioning-aided benefits made available to multi-connectivity IIoT device operation at 28GHz, which notably improve data transfer rates, communication latency, and extent of control overhead..
Published in Communications Magazine in November 2018
Videos and Demonstrations
3D Drone Positioning
Example 3D positioning demonstration of a drone flying through the METIS Madrid Map. The trajectory of the drone contains a take-off in the beginning as well as a short landing in the middle of the trajectory. The continuous tracking of the drone is carried out by fusing either only direction of arrival (DoA) estimates or both DoA and time of arrival (ToA) estimates from two closest line of sight base stations in DoA-only or Pos&Sync extended Kalman filter (EKF), respectively.