Energy Efficient Power Allocation for Cognitive Radio Networks with Optimal Spectrum Utilization using Ensemble Adaptive Neuro Fuzzy Inference System

Radio Spectrum (RS) is underutilized by primary licensed users. Though many techniques for effective use of RS exist, OSA (Opportunistic Spectrum Access) has been most feasible in optimizing spectrum utilization as they allow unlicensed users access RS opportunistically. OSA approaches use CR (Cognitive Radios) which sense unused spectrum and familiarize their operating characteristics accordingly in real time environments. A recent study proposed spectrum access control and RS use by secondary users using probabilistic neural networks. The work also introduced an enhanced IDS (Intrusion Detection System) using Improved Support Vector Machine (ISVM )to identify anomalies in network’s behaviour after learning normal behaviour from network traffic flows, protocol operations and primary user access times. Energy efficiency, an important aspect of CRNs (Cognitive Radio Networks) was not catered to in this study. This paper proposes a model for optimal Spectrum Utilization of wireless systems with CRNs where antecedents are also regarded for selection of spectrum bands. Anomalous behaviours in networks are also identified. Additionally this work introduces an energy efficient framework for power allocation to secondary users.