Harmonic Retrieval Based Baseband Channel Estimation for Millimeter Wave OFDM Systems

For massive multi-input multi-output (MIMO) enhanced millimeter wave (mmWave) frequency-division multiplexing (OFDM) systems, channel estimation (CE) is challenging. In this paper, the baseband CE of mmWave based MIMO-OFDM systems after beam searching is formulated as a harmonic retrieval (HR) problem, where each path of the channel represents a harmonic with its frequency and strength to be estimated. We propose two methods, a windowed orthogonal matching pursuit (window-OMP) method and a windowed discrete Fourier transform (window-DFT) method, to approximately acquire the maximum likelihood (ML) estimate of the baseband CE. The window-OMP method is capable of approximating the ML estimator with high accuracy, while the window-DFT method has a lower complexity and is shown to acquire approximate ML estimate under the assumption that the frequencies of harmonics are sufficiently separated. Theoretical analysis is performed to derive a closed-form Cramér–Rao lower bound as well as to investigate the effect of wrong paths to the estimation accuracy. A simulation study is conducted to investigate the performance of the proposed methods, and the results obtained verify that our methods outperform the existing estimation of signal parameters by rotational invariant techniques based HR method and the conventional interpolation method.