Neuro Fuzzy Based Vertical Handoff Decision Algorithm for Wireless Heterogeneous Networks

Abstract

The next generation of wireless communication systems, called beyond third generation (B3G) or fourth generation (4G), will involve the integration of diverse but complementary cellular and wireless technologies, all of which will coexist in a heterogeneous wireless access environment. One of the major design issues in heterogeneous wireless networks is the support of vertical handoff, vertical handoff occurs when a mobile terminal switches from one network to another. More intelligent vertical handoff algorithms which consider user profiles, application requirements, and network conditions must be employed in order to provide enhanced performance results for both user and network. Handoff decision is the ability to decide when to perform the vertical handoff and determine the best handoff candidate access network. This paper provides vertical handoff decision algorithm that enables wireless access network selection at a mobile terminal using neuro fuzzy model and self evolving evolutionary learning. Our proposed vertical handoff decision algorithm is able to determine when a handoff is required, and selects the best access network that is optimized to network conditions, quality of service requirements, mobile terminal conditions, user preferences, and service cost. The results demonstrate the comparison of the optimized ANFIS with PSO, CPSO and with hybrid evolutionary algorithm of cultural cooperative particle swarm optimization (CPSO) and cultural algorithm (CA).