A Novel ANN based Efficient Proactive Handoff Scheme for Cognitive Radio Network
Vaishali Agarwal, Abhay Kumar, Debyansh Kumar, Palak Tripathi, Vivek Rajpoot, Vijay Shanker Tripathi · 2019 International Conference on Computing, Power and Communication Technologies (GUCON) · 2019
Cognitive radio (CR) shows a global acceptance in the dynamic spectrum allocation scenarios. Cognitive Radio networks (CRNs) consists of secondary user (SU) that exploit the vacant spectrum of the primary user (PU), opportunistically. In CRN, spectrum handoff process (SHP) is an integral part and one of the most important tasks for functioning. The performance of CRN is greatly affected by handoff. The efficient selection of vacant channels for handoff is an important issue to be investigated by researchers. The unavailability of vacant channel for handoff may cause termination communication link. To address the stated problem, an artificial neural network (ANN) based proactive handoff scheme for figuring out the best candidate channels is proposed. The past indices of primary user (PU) activity is licensed channel is utilized to train the neural network. The list of channels, ranked on the basis of least probability of occupancy by PU is obtained. This ranked list is used by CR user to obtain the best future channel for handoff. The performance shows improvement in average throughput and delay parameters as the required number of handoffs in the scenario become less. Maximum 46.15% improvement as compare to IEEE 802.11 is observed at highest packet generation rate. Likewise 38% to 47% reduction in required no. of handoff is visible.