A Hybrid Model for User History-BasedPrediction with Geolocation Assisted Handover in 5G
Safa Abdalla (University of Technology Malaysia, Malaysia); Sharifah Ariffin (University of Technology Malaysia, United Kingdom (Great Britain))
The upcoming years promised with an explosive growth in data traffic for mobile real-time applications. Femtocell networks seem to be the solution for the demanding traffic and coverage required in the next generation of telecommunication. However, the ultra-dense of the femtocellular networks bring additional delay overhead due to unnecessary handovers for the roaming Mobile Station (MS). This paper presents a hybrid model to predict the users movements accurately and eliminate the unnecessary handovers . The proposed model consider the behavioral patterns of MS movements which decreasing the delay to suit the real time application, and result of enhancing the performance in 5G networks.
Journal: International journal of simulation: systems, science & technology V18
Published: Dec 30, 2017