Overhead-Free Blockage Detection and Precoding Through Physics-Based Graph Neural Networks: LIDAR Data Meets Ray Tracing

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