Subarray-Aware Beam-Split Pattern Detection for Near-Field XL-MIMO Channel Estimation

In this correspondence, we investigate the uplink channel estimation for mmWave extremely large-scale multiple-input multiple-output (XL-MIMO) communication system. Our primary emphasis is on addressing the near-field effects that arise in wideband scenarios, including spherical wave propagation, spatial non-stationarity, and beam-split effect. As a solution, we propose an innovative subarray-aware channel estimation approach based on beam-split pattern detection. Our approach leverages a meticulously designed sensing matrix to extract subarray signals and perform individual wideband channel estimation for each subarray. Corroborated by the Cramér-Rao lower bound (CRLB), simulation results show that the proposed scheme outperforms benchmark techniques in terms of normalized mean square error (NMSE) performance while maintaining comparable computational complexity.