Modular XL-Array-Enabled Channel Estimation and Localization in Terahertz Systems

This work considers the three-dimensional (3-D) positioning problem in a Terahertz (THz) system enabled by a modular extra-large (XL) array with sub-connected architecture. Our purpose is to estimate the channel parameters and Cartesian Coordinates of multiple user equipments (UEs) based on the received signal of the RF chains while considering the spatial non-stationarity (SNS). We apply the hybrid spherical-planar wave model (HSPWM) owing to the structural feature of the modular array, and propose a 3-D localization algorithm with relatively high accuracy and low complexity. Specifically, we first distinguish the sub-arrays (SAs) located in the VR as anchors, and select typical anchors with the largest receive power. Then, we estimate the angles-of-arrival (AoAs) from each UE to typical anchors via compressed sensing (CS) method, while the channel attenuation coefficients are obtained through least square (LS) method. In addition, we apply the weighted least square (WLS) method to obtain a coarse 3-D position estimation of each UE according to the AoA estimations. Finally, we estimate the AoAs and attenuation coefficients of the other anchors with a reduced dictionary (RD)-CS-based method for lower computational complexity, and utilize all the efficient AoA estimations to derive a fine position estimation. Simulation results indicate that the modular XL-array-enabled channel estimation and positioning framework can achieve satisfactory positioning accuracy with evident reduction in complexity.