Research Article
Neural networks for adaptive vertical handover decision
@INPROCEEDINGS{10.1109/WIOPT.2007.4480068, author={Sana Horrich and Sana Ben Jemaa and Philippe Godlewski}, title={Neural networks for adaptive vertical handover decision}, proceedings={5th International ICST Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks}, publisher={IEEE}, proceedings_a={WIOPT}, year={2008}, month={3}, keywords={Fuzzy logic Handover decision Heterogeneous networks Mobility management Neural networks inversion Radio resource management}, doi={10.1109/WIOPT.2007.4480068} }- Sana Horrich
Sana Ben Jemaa
Philippe Godlewski
Year: 2008
Neural networks for adaptive vertical handover decision
WIOPT
IEEE
DOI: 10.1109/WIOPT.2007.4480068
Abstract
This paper focuses on mobility management between heterogeneous radio access networks (RANs). A fuzzy multi- criteria vertical handover algorithm enhancing the handover performance is proposed. This algorithm is based on fuzzy logic control. The fuzzy logic controller (FLC) takes into account multiple relevant criteria and rules based on prior knowledge of the network. A multi-layer perceptron (MLP) neural network is trained in order to learn the relationship between the FLC parameters and throughputs on UMTS and WLAN. Then, MLP inversion is performed in order to obtain the optimal parameters of the membership functions starting from throughput objective values. The performances of our handover algorithm are evaluated and compared to a conventional vertical handover algorithm by means of simulations. The proposed handover algorithm improves the network performances.