Harmonic Retrieval Based Baseband Channel Estimation for Millimeter Wave OFDM Systems

Abstract

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 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 (CRLB) 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 (ESPRIT) based HR method and the conventional interpolation method.

5G Positioning and Mapping With Diffuse Multipath

“…the channel response in frequency domain for sub-carrier i with frequency f i is represented as [33] H…”

5G Positioning and Mapping with Diffuse Multipath

“…the channel response in frequency domain for sub-carrier i with frequency f i is represented as [27]…”

A Novel NE-DFT Channel Estimation Scheme for Millimeter-Wave Massive MIMO Vehicular Communications

“…the high maneuverability of the vehicle network, the beamforming needs to be completed in a short time, the channel coherence time between the base station (BS) and the mobile users (MS) is greatly reduced [8]- [10] and useful signals in the channel are susceptible to noise interference [11]- [14]. Fortunately, the benefit of the high directional power gain of beamforming can sufficiently compensate for the high path loss in the mmWave band, which guarantees a high signal-tonoise ratio (SNR) at the receiver to support extremely high data rate transmissions with large bandwidths [15], [16].…”

“…In [7], [19], [20], the authors pointed out that mmWave massive MIMO communication is the only feasible way to achieve high-bandwidth connected vehicles. The authors in [12], [14] considered some key parameters affecting channel estimation accuracy, such as Doppler frequency, antenna patterns, etc. Moreover, the authors of [7] and [17] proposed to incorporate nested arrays into the analog array architecture in high-speed scenarios, and these schemes can effectively reduce the complexity and power consumption of the system.…”

“…Moreover, the authors of [7] and [17] proposed to incorporate nested arrays into the analog array architecture in high-speed scenarios, and these schemes can effectively reduce the complexity and power consumption of the system. In addition, some works studied the channel estimation schemes in high-mobility vehicle cellular systems, such as the proposal of the authors in [6], in which a 3D structured orthogonal matching pursuit algorithm-based downlink channel estimation technique in high-mobility scenarios was reported that can achieve accurate CSI with low pilot overhead, and the work of [14] that transformed the channel estimation problembased mmWave-OFDM system into a harmonic retrieval problem and proposed two methods to approximately acquire the maximum likelihood (ML) estimate. Unfortunately, existing schemes only considered the analog beamforming cases, which limited the processing capability of mmWave transceivers and caused a considerable performance loss, particularly for mobile users.…”