Situational awareness for autonomous ships in the Arctic:mMTC direct-to-satellite connectivity

• Main Authors: Asad Ullah, M. (Muhammad), Yastrebova, A. (Anastasia), Mikhaylov, K. (Konstantin), Höyhtyä, M. (Marko), Alves, H. (Hirley)
• Format: Article in Journal/Newspaper
• Language: English
• Published: Institute of Electrical and Electronics Engineers 2022
• Subjects: Arctic; Autonomous vehicles; Marine vehicles; Resource management; Safety; Satellites; Traffic control; Transportation
• Online Access: http://urn.fi/urn:nbn:fi-fe2022082255936

Abstract The maritime autonomous surface ship (MASS) promises a revolution in naval logistics by offering sustainability, safety, and operational costs reduction. The MASS can bring to the Arctic and other hard-to-reach regions numerous social and economic benefits, thus contributing to equalizing access for human and machine terminals to connectivity, and equate the life quality of their inhabitants with that of other regions. In this article, we suggest a hybrid communication architecture that separates a ship’s data traffic into awareness and emergency components. For the former traffic, we advocate the possibility of direct-to-satellite using massive machine-type communication (mMTC) and low-power wide-area network (LPWAN) technologies. To validate this hypothesis and investigate the potential performance and effect of different design and configuration parameters, we conduct simulations based on real-life positions of ships and satellites, traffic patterns, and the LoRaWAN connectivity model. Our results demonstrate the suggested approach’s feasibility and clarify the different parameters’ effects on the connectivity performance for the classical LoRa and novel long-range frequency hopping spread spectrum modulation coding schemes. Notably, the combination of multi-connectivity of LoRaWAN LPWAN technology and multi-satellite visibility dramatically boosts the probability of packet delivery.