Reduced-Complexity Channel Estimation by Hierarchical Interpolation Exploiting Sparsity for Massive MIMO Systems with Uniform Rectangular Array

Angle reciprocity is an important property adopted for massive MIMO channel estimation. For systems equipped with uniform rectangular antenna array, two-dimensional fast Fourier transform (2D-FFT) is often employed to transform the information in the spatial domain to the angular domain. To save the complexity, we propose hierarchical channel interpolation algorithm by exploiting the channel sparsity in the millimeter wave frequency band. Local interpolation with fine resolution is only applied to the selected regions determined from the coarse interpolation for obtaining required angular information so as to eliminate the unnecessary computations. Furthermore, the interference caused by the energy leakage from the adjacent paths is cancelled to acquire better estimation results of path gains. From the performance simulation results, the proposed algorithm can achieve better channel estimation performance than the zero-padded and phase-rotated 2D-FFT algorithms with reduced complexity for acquiring angular information.