Mike Koivisto, Jukka Talvitie, Elizaveta Rastorgueva-Foi, Yi Lu, and Mikko Valkama
Already in the beginning of the fifth generation (5G) standardization process, positioning has been considered as a key element in future wireless networks. In order to perform accurate positioning, solutions for estimating and processing positioning related measurements such as direction of arrival (DoA) and time of arrival (ToA) for various use-cases needs to be developed. Building on the existing 5G new radio (NR) specifications and millimeter wave frequencies, we propose a novel estimation and tracking solution of the DoA and ToA for a system with analog beamforming capabilities. In addition to the proposed extended Kalman filter (EKF)-based estimation approach, we derive Cramér-Rao lower bounds (CRLBs) for the considered multi-beam system, and propose an information-based criterion for selecting the necessary beams for the estimation process in order to provide highly accurate performance with feasible computational complexity. The performance of the proposed method is evaluated using extensive ray-tracing simulations and numerical evaluations, and the results are compared with other estimation and beam-selection approaches. Based on the obtained results, beam-selection at the receiver can have a significant impact on the DoA and ToA estimation performance as well as on the subsequent positioning accuracy.
Submitted to IEEE Transactions on Wireless Communications
Videos and Demonstrations
3D TX positioning in multi-RX scenario.
In this demonstration, the TX node that is attached to a vehicle is moving along a pre-determined trajectory and following a realistic acceleration profile. Every 100 ms, the TX transmits uplink sounding reference signals (SRS) through a short beam-sweep process exploiting only 8 beams at the TX-side. These signals are then received by the RX-nodes which are then estimating the considered channel parameters (ToA and DoA angles). The obtained estimates are finally used in the joint TX positioning and synchronization either in a single RX or in a centralised node depending on the deployment. The positioning performance of the proposed cascaded EKF algorithm is visualized for two different system setups. In the first setup, TX positioning is carried out using two RXs, whereas in the second setup, ToA and DoA estimates from three RXs are fused in TX positioning. The participating RX nodes are all in line-of-sight (LoS) condition and their participation in the positioning phase is determined based on the observed SNRs.
Joint 3D TX positioning and synchronization in multi-RX scenario.
In this demonstration, the setup is similar to that of presented above except the RXs are assumed to be mutually synchronized, whereas the TX clock is assumed to follow a first-order auto-regressive model with a time-varying clock offset.