User Equipment Tracking for a Millimeter Wave System Using Vision and RSSI

Abstract

In a mobile millimeter wave (mmWave) communication system, blockages cause disconnections or serious degradation of communications. Several techniques have been proposed to control radio links between multiple base stations based on blockage prediction using camera images to avoid these problems. However, blockage prediction requires continuously determining the position of user equipment (UE) with decimeter precision, which is difficult when sensors and resources on the UE side are not available, and there are many moving objects around the UE. To resolve this problem, we propose a UE tracking method that uses a received signal strength indicator (RSSI) and RGB-D camera images from the base station. The proposed method consists of a combination of visual tracking and reidentification of the UE using radio information and camera images. We use the synchronization of the RSSI variation with the occlusion on the image by movements of the UE and objects for reidentification. We evaluated the proposed method experimentally in an outdoor environment by simulating a communication area formed by mmWave band base stations. The proposed method achieved an 11.5% improvement in tracking accuracy compared with conventional visual tracking.INDEX TERMS Image analysis, millimeter wave communication, object tracking,

Outage-Minimization Coordinated Multi-Point for Millimeter-Wave OFDM With Random Blockages

“…The method in [35] exploits mmWave in-band signatures to provide high prediction accuracy using machine learning with received signal power sequences. To further enhance the prediction accuracy, a technique to track positions of user equipments (UEs) via received power and visual images has been studied [37]. Based on the prediction of the instantaneous blockage occurrence, handover strategies have been proposed in [33], [34].…”