Detecting Human Blockage and Device Movement in mmWave Communication System

The mmWave communication system is operating at a regime with high number of antennas to extend the communication range and to recover the high path loss. Before any communication starts, devices are needed to align their beam pointing angles towards each other. The best beam pointing angles are obtained through BeamForming (BF) training protocol. If the communication environment and devices are stationary, the training results can stay valid for a long period of time. However, the environment is very dynamic. Device movement and human blockage in the link may invalidate the BF training results. Prior work focuses on improving training time when a specific type of errors happens. For example, switching to alternative paths is suggested when human blockage occurs. However, solutions that tackle a type of error are not compatible with others. Therefore, it is important to identify the type of occurring beam errors before applying any remedies. In this paper, we propose a linear dynamical system model to demonstrate the dynamics of the occurring errors due to link blockage and device movement. By using the model, we show that it is hard to estimate the errors purely based on the observable quantity provided. To solve this, we propose two probing protocols that consume very few network resources but are effective in identifying the beam errors as well as correcting them. The simulations show that it effectively handles the beam errors and only consumes 3% of network resources while more than 30% resources are required in the prior work for a fast moving device experiencing occasional link blockage.