Proactive Base Station Selection Based on Human Blockage Prediction Using RGB-D Cameras for mmWave Communications

This paper proposes a proactive base station selection system for millimeter-wave (mmWave) communications based on human blockage prediction using RGB and depth (RGB-D) cameras. In mmWave communications, the frame loss rate increases and the throughput sharply decreases if a pedestrian blocks a line-of-sight (LOS) path between a station and a base station.To address this human blockage problem, multiple base stations can be arranged so as to maintain at least one LOS path.For base station selection in particular, RGB-D camera images can be used to estimate the mobility of pedestrians and to predict when blockage of LOS paths will occur. Using IEEE 802.11ad-based wireless local area network (WLAN) devices, a testbed for implementing the proposed system was built. The results of experiments on the influence of human blockage confirmed the presence of significant throughput degradation due to human blockage.Furthermore, the innovative experimental results demonstrated that the proactive base station selection system can considerably reduce the duration of human blockage-induced degradation of throughput performance relative to reactive base station selection systems based on throughput performance.