DFrFT-Based Near-Field Channel Estimation for Extremely Large-Scale MIMO Systems

To deal with channel estimation in the near-field area, previous studies have introduced orthogonal matching pursuit (OMP)-based algorithms, which are generally with high computational overhead. To tackle this issue, a novel approach based on discrete fractional Fourier transform (DFrFT) called DFrFT-clean is proposed in this paper. Instead of employing OMP, our method identifies the peaks of the DFrFT of the processed received signal to estimate the parameters of each path component of the channel. Additionally, it implements a cleaning procedure to mitigate the interference of strong paths on weaker paths. Simulation results show that the proposed DFrFT-clean method can significantly reduce the computational complexity while maintaining comparable or even favorable normalized mean square error (NMSE) performance compared to the benchmark algorithms.