Optimized Handoff with Mobility Prediction Scheme Using HMM for femtocell networks

Ahlam Ben Cheikh (1, 2) , Mouna Ayari (1, 2) , Rami Langar (1) , Guy Pujolle (1) , Leila Azouz Saidane (2)

1 Phare
2 CRISTAL - Centre de Recherche Réseau Image SysTème Architecture et MuLtimédia

In this paper, we propose a new approach for optimizing the handoff decision in femtocell networks using Hidden Markov Model. To do so, we formulate the handoff problem as an optimization problem whose objective is to find the best Femtocell Access Point (FAP) assignment strategy that minimizes the number of unnecessary handoffs while maintaining a good quality of wireless communications. We have used Hidden Markov Model prediction tools to predict the target FAP by observing the geographic positions of the mobile. To evaluate the effectiveness of our proposal, we conducted extensive simulations. Results show that our proposed approach minimizes the number of handoffs by up to 7 times and enhances the dwell time in the FAP by up to 42% in comparison with others handoff decision making strategies commonly used in related cellular modeling works.

Mots clés: Femtocells; Handover; Handoff optimization; Mobility Prediction; Hidden Markov Model.

Domaines: Informatique [cs]

Ahlam Ben Cheikh, Mouna Ayari, Rami Langar, Guy Pujolle, Leila Azouz Saidane. Optimized Handoff with Mobility Prediction Scheme Using HMM for femtocell networks. 2015 IEEE International Conference on Communications (ICC), Jun 2015, Londres, United Kingdom. pp.3448-3453, ⟨10.1109/ICC.2015.7248858⟩. ⟨hal-01199686⟩