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The Integrated History_based Prediction for Future Networks

Future communications technology is introduced to meet the explosive demand for high-speed data rate from a mobile broadband user. The heterogeneity of the wireless networks involves the integration of small cells for the demand for high data rate and good QoS, to support multimedia streaming at precision levels. However, seamless mobile access is a major challenge in next-generation networks. Many research trends were introduced to enhance the performance of handover to upgrade towards the future. However, prediction schemes are considered to be as a promising direction that solves many mobility issues. Knowing a user’s next cell allows more efficient resource allocation and enables new location-aware services. By anticipating the target cell for the user’s movement, the resource allocation can be performed before the actual handover, thus can reduce delays in resource allocation and finally can reduce the latency. In this paper, we proposed an integrated mobility prediction. The prediction scheme considers the regularity and randomness in the user behavior through using local and global profile. The simulation works reveal outperformance in prediction accuracy, unnecessary handover, and delay.