SPIN: Synchronization Signal-Based Positioning Algorithm for IoT Nonterrestrial Networks

Nonterrestrial networks (NTNs) complement the terrestrial cellular networks by extending coverage to the user equipments (UEs) located in unserved and underserved areas. One of the most critical problems faced by NTN UEs is the lack of uplink (UL) synchronization and the associated initial access failure resulting from the high Doppler frequency offset caused by satellite velocity. While NTN new radio (NR) UEs rely on the global navigation satellite system (GNSS) to resolve the UL synchronization problem, it is not always feasible for power-critical NTN Internet of Things (IoT) UEs. To this end, we design synchronization signal-based positioning in IoT NTNs (SPIN) which enables the IoT UEs to tackle the UL synchronization problem. SPIN estimates position and velocity of the UE using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements on the downlink synchronization signals. Consequently, the UEs can use the position and velocity estimates to compute and compensate for the residual time and frequency offsets, thereby successfully synchronizing to the NTN UL. We conduct physical layer and system-level simulations to show the effectiveness of our solution. SPIN positioning accuracy achieves the Cramér-Rao lower bound and meets the target accuracy required for UL synchronization. We also compare the battery life of an NTN IoT UE which uses SPIN for UL synchronization with that of a UE using GNSS-based solution. Our numerical results show that SPIN has significant battery life savings over GNSS-based solution while also maintaining a low computational complexity.