  Intelligent reflecting surface (IRS) offers a cost effective solution to link
blockage problem in mmWave communications, and the prerequisite of which is the
accurate estimation of (1) the optimal beams for base station/access point
(BS/AP) and mobile terminal (MT), (2) the optimal reflection patterns for IRSs,
and (3) link blockage. In this paper, we carry out beam training design for
IRSs assisted mmWave communications to estimate the aforementioned parameters.
To acquire the optimal beams and reflection patterns, we firstly perform random
beamforming and maximum likelihood estimation to estimate angle of arrival
(AoA) and angle of departure (AoD) of the line of sight (LoS) path between
BS/AP (or IRSs) and MT. Then, with the estimate of AoAs and AoDs, we propose an
iterative positioning algorithm that achieves centimeter-level positioning
accuracy. The obtained location information is not only a fringe benefit but
also enables us to cross verify and enhance the estimation of AoA and AoD, and
facilitates the prediction of blockage indicator. Numerical results show the
superiority of our proposed beam training scheme and verify the performance
gain brought by location information.
