Position-Aided Compressive Channel Estimation and Tracking for Millimeter Wave Multi-User MIMO Air-to-Air Communications

We consider a multi-user (MU) millimeter wave (mmWave) network of aerial vehicles. One aircraft acts as an access point that communicates with multiple airborne users through mmWave communication links. We focus on the problem of estimating and tracking the multi-user mmWave frequency- selective MIMO channel, leveraging prior information about the position and trajectory of each user (aerial vehicle). We develop a channel estimation and tracking strategy based on compressed sensing tools which introduces a low overhead, even when operating in the high mobility aerial scenario. We show by simulation that, even with a reduced number of training symbols and in the low SNR regime, the new channel estimation and tracking algorithm provides channel state information (CSI) of enough quality to obtain and maintain near-optimal values of spectral efficiency.