2D Block OMP for Near-Field Channel Estimation with Extremely Large-Scale UPA
Channel estimation for extremely large-scale uniform planar arrays (UPAs) requires exploiting near-field channel structure to reduce pilot overhead. With a specifically devised channel representation matrix, the near-field channel exhibits a 2D sparse structure, which a conventional 1D block partition might divide into multiple groups. This work develops a 2D block orthogonal matching pursuit (2D-BOMP) estimator that exploits this structure through rectangular coefficient grouping. We establish sufficient recovery conditions for noiseless and noisy measurements and compare the sufficient pilot-length requirements of 1D and 2D partitions. Numerical simulations demonstrate the estimation benefits of 2D-BOMP in estimating the near-field channels of large-scale UPAs, compared with the conventional 1D-BOMP as well as the polar-domain based OMP method.