Channel Estimation by Using a 2D DFT for Millimeter-Wave Systems

The usage of the millimeter wave (MMW) band in the 5th generation (5G) networks relies on beamforming to compensate the strong path-loss suffered at higher frequencies. To properly exploit the beamforming implemented in multiple antenna devices, proper algorithms to track and estimate the channel need to be designed. In this work we propose a novel channel estimation method for MMW systems where both transmitter and receiver are equipped with less radio frequency chains than antennas and implement hybrid analog-digital beamforming. First, we define a training sequence which includes a set of analog and digital beamformers to probe the channel. Then, we develop an iterative algorithm which exploits the sparse nature of the MMW channel and is based on the two dimensional (2D) discrete Fourier transform (DFT) of the received training samples. Numerical results show the effectiveness of the proposed channel estimation method even in low signal to noise ratio (SNR) conditions.