Compressive estimation of near field channels for ultra massive-MIMO wideband THz systems

In this paper, we develop a channel estimation strategy for terahertz (THz) ultra-massive multiple-input multiple-output (UM-MIMO) system with a sub-connected array-of-subarrays architecture, in which one subarray (SA) is connected to one RF chain exclusively. Further, we consider a hybrid spherical-planar wave model (HSPM) for the channel modeling in which the channel between individual transmit and receive SAs is based on the planar wave model, while variation across the SAs is captured via the spherical wave model. Since the channel between different SAs is similar - albeit not identical - we propose a dictionary reduction based compressed sensing method to exploit the spatial information extracted from the estimates of the first SA in channel estimation of subsequent SAs. The proposed method achieves up to $\unit[2]{dB}$ NMSE improvement over the conventional methods.