Blockage Prediction for Millimeter-wave Communications Based on People Flow Data

This paper proposes a novel method for deriving the average blockage duration based on time-series prediction of future pedestrians using people flow data toward reliable millimeter-wave communications. The issue is to stably predict pedestrian conditions, which are the main cause of the blockage, in a realistic environment. Therefore, we utilize time-series data on people flow in an area, to predict the future state of pedestrians. The average walking speed in the area is calculated by giving the predicted values of traffic flow to pedestrian models. Furthermore, we define the occurrence of blockage as the existence of a pedestrian in the first Fresnel zone, and based on the above information, we calculate the estimated value of the time-series data of the average blockage duration in the area. In this paper, we evaluate the method via human blockage experimental measurements and computer simulations.