RIS-Enabled NLoS Near-Field Joint Position and Velocity Estimation under User Mobility

Artikel i vetenskaplig tidskrift, 2024

In the context of single-(BS) nonline- of-sight (NLoS) single-epoch localization with the aid of a reflective (RIS), this paper introduces a novel three-step algorithm that jointly estimates the position and velocity of a mobile (UE), while compensating for the Doppler effects observed in (NF) at the (RIS) elements over the short transmission duration of a sequence of (DL) pilot symbols. First, a low-complexity initialization procedure is proposed, relying in part on (FF) approximation and a static user assumption. Then, an alternating optimization procedure is designed to iteratively refine the velocity and position estimates, as well as the channel gain. %, at every step along the way. The refinement routines leverage small angle approximations and the linearization of the (RIS) response, accounting for both NF and mobility effects. We evaluate the performance of the proposed algorithm through extensive simulations under diverse operating conditions with regard to (SNR), (UE) mobility, uncontrolled multipath and (RIS)-(UE) distance. %We evaluate the performance of the proposed algorithm by means of simulations in a canonical scenario and Our results reveal remarkable performance improvements over the (SoTA) mobility-agnostic benchmark algorithm, while indicating convergence of the proposed algorithm to respective theoretical bounds on position and velocity estimation. %[BD: I remember we had this discussion with CHAL about the use of Algo1 as a variant of an existing algo (in 1st approximation). Does it still hold?], illustrating the dominating impact of the distance to the (RIS), as well as of (UE) velocity.