Coordinated handover optimization in heterogeneous network scenario using deep learning

Traditional signal-based handover may not ensure best user experience in terms of throughput, packet loss or latency. We are developing a deep learning-based handover technique using coordinated feedback from the associated users and the base stations. We have used LSTM based sequential classification to choose the optimum network to handover for various type of user based on their unique QoS requirement.