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Hybrid analog/digital beamforming is a promising technique to realizemillimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systemscost-effectively. However, existing hybrid beamforming designs mainly rely onreal-time channel training or beam sweeping to find the desired beams, whichincurs prohibitive overhead due to a large number of antennas at both thetransmitter and receiver with only limited radio frequency (RF) chains. Toresolve this challenging issue, in this paper, we propose a newenvironment-aware hybrid beamforming technique that requires only lightreal-time training, by leveraging the useful tool of channel knowledge map(CKM) with the user's location information. CKM is a site-specific database,which offers location-specific channel-relevant information to facilitate oreven obviate the acquisition of real-time channel state information (CSI). Twospecific types of CKM are proposed in this paper for hybrid beamforming designin mmWave massive MIMO systems, namely channel angle map (CAM) and beam indexmap (BIM). It is shown that compared with existing environment-unaware schemes,the proposed environment-aware hybrid beamforming scheme based on CKM candrastically improve the effective communication rate, even under moderate userlocation errors, thanks to its great saving of the prohibitive real-timetraining overhead.

Environment-Aware Hybrid Beamforming by Leveraging Channel Knowledge Map