Presence of multiple networks in a particular area is a very common real time scenario, due to this there is a presence of multiple service providers which can serve a particular node`s communication needs. Taking a handoff decision in such a complicated heterogeneous network scenario is tricky at both node and network level, as the nodes demand higher QoS while the network demands optimum number of nodes for service. To solve this complex problem, we propose a deep learning based approach which minimizes the false handoffs in the network, and reduces the delay needed during the handoff procedure. Our observations show that there is a 10% reduction of number of unnecessary handoffs in the network, and more than 8% reduction in handoff decision delay as compared to the existing game theory based algorithms.

Heterogeneous, handoff, deep learning, QoS, delay

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