We use the synchronization of the RSSI variation with the occlusion on the image by movements of the UE and objects for reidentification. The proposed method consists of a combination of visual tracking and reidentification of the UE using radio information and camera images. 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. 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. Several techniques have been proposed to control radio links between multiple base stations based on blockage prediction using camera images to avoid these problems. In a mobile millimeter wave (mmWave) communication system, blockages cause disconnections or serious degradation of communications. The results reveal that the proposed positioning method for LTE networks outperforms the CID based positioning method and can be used in the practical localization applications in LTE networks. The performance of the proposed positioning method is obtained in terms of cumulative distribution function (CDF) and the results are compared with the CID based positioning method which is currently employed on serving mobile location center (SMLC). The proposed positioning method is evaluated by using real measurement data which are collected in Istiklal Street, Istanbul, Turkey where the COST 231 Walfish-Ikegami path loss model is applicable. The distance between serving eNodeB and user equipment (UE) is calculated using RSRP and COST 231 Walfish-Ikegami path loss model, and based on the distance calculation, the position of UE is calculated using the azimuth and beamwidth values of the serving eNodeB. In this paper, we propose a novel enhanced cell ID (E-CID) based positioning method for LTE network using reference signal received power (RSRP), azimuth parameters and COST 231 Walfish-Ikegami path loss model.

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