Intelligent Radio Network Selection for Next Generation Wireless Networks
931
Mohammed M. Alkhawlani
Faculty of Science and Engineering, University of Science and Technology, Sana'a, Yemen
Abstract
Next Generation Wireless Network (NGWN) will be composed of multiple radio access technologies (RATs), therefore new radio resource management (RRM) schemes and mechanisms are necessary to benefit from the individual characteristics of each RAT and to exploit the gain resulting from jointly considering the whole set of available radio resources in each RAT. Radio Network Selection is the RRM mechanism responsible for selecting the most optimal and promising RAT for a new service request in the NGWN. This paper presents and designs an intelligent multi criteria RNS solution that considers NGWN environment with a co-existed WWAN, WMAN, and WLAN. The proposed solution uses a combined parallel fuzzy logic control and Analytic Hierarchy Process (AHP) system to achieve scalable, flexible, general, and adaptable solution. The simulation results show that the developed algorithm has better and more robust performance over the random selection algorithm, the terminal speed based selection algorithm, and the service-type based selection algorithm that are used as reference algorithms.
Next Generation Wireless Network (NGWN) will be composed of multiple radio access technologies (RATs), therefore new radio resource management (RRM) schemes and mechanisms are necessary to benefit from the individual characteristics of each RAT and to exploit the gain resulting from jointly considering the whole set of available radio resources in each RAT. Radio Network Selection is the RRM mechanism responsible for selecting the most optimal and promising RAT for a new service request in the NGWN. This paper presents and designs an intelligent multi criteria RNS solution that considers NGWN environment with a co-existed WWAN, WMAN, and WLAN. The proposed solution uses a combined parallel fuzzy logic control and Analytic Hierarchy Process (AHP) system to achieve scalable, flexible, general, and adaptable solution. The simulation results show that the developed algorithm has better and more robust performance over the random selection algorithm, the terminal speed based selection algorithm, and the service-type based selection algorithm that are used as reference algorithms.
Keywords: radio network selection, NGWN, fuzzy logic, AHP, common radio resource management