  In this letter, we address blockage detection and precoder design for
multiple-input multiple-output (MIMO) links, without communication overhead
required. Blockage detection is achieved by classifying light detection and
ranging (LIDAR) data through a physics-based graph neural network (GNN). For
precoder design, a preliminary channel estimate is obtained by running ray
tracing on a 3D surface obtained from LIDAR data. This estimate is successively
refined and the precoder is designed accordingly. Numerical simulations show
that blockage detection is successful with 95% accuracy. Our digital precoding
achieves 90% of the capacity and analog precoding outperforms previous works
exploiting LIDAR for precoder design.
