Direction prediction assisted handover using the multilayer perception neural network to reduce the handover time delays in LTE networks

Abstract

Nowadays, the rapid increase in the development of the wireless communication, the Evolved Universal Terrestrial Radio Access (E-UTRA) of the Long Term Evolution (LTE) is more improved and modern technology compared with the WiMAX technology. The researchers discussed the accurate and fast handover in the LTE in the recent years. Moreover, the researchers of the evolved Node B(eNB) proposed the history of the UE visited base stations and the use of their information just to consider the target in the case of handover. While the identification of the cell and their times were kept inside the cell of the base station. In this paper, an advanced technique using the historical information to reduce the handover time delay as much as possible depending on the packet loss, the time required for the base station to reply and the region domain as much as the time domain. In conclusion, the angle of the situated target base station is computed and the distance to that base station is taken into consideration for cutting down more and more real-time of the handover procedure in the LTE system. The simulation results showed that the proposed model is more efficacious in decreasing the handover time delay by skipping unwanted base station according to their angles.