An improved vertical handoff decision based on the modular neural network with fuzzy logic for wireless heterogeneous network

In recent times, provision of required services to consumers on an anyplace any time basis is limited by several constraints one among which is the issue of call drop. In order to eliminate this situation, the network operator should enhance vertical handoff (VHO) mechanism. VHO is the process of exchanging the ongoing wireless link to any of the wireless technologies in heterogeneous to support node mobility without fail. Normally, a mobile user can achieve VHO process by utilising the received signal strength (RSS) as single criteria. But sometimes it leads to abortive handoff, service disruption and unbalanced network load. In this paper, a modified modular neural network into fuzzy logic (MNN-FL) by using multi criteria metrics in the mobile environment is proposed. State of mobile terminal (MT) is evaluated by fuzzy logic (FL) by comparing the battery level and the mobility of MT in which identification of best access network is achieved. The high value SNRs are considered for choosing the best network access to accomplish higher data rates and throughput. The performance results demonstrates that MNN-FL-based VHDA shows well-organised network concert in terms of handoff dropping rate and enhanced throughput than existing VHO algorithms.