Abstract
Detection of high energy using spectrum sensing step especially when using a collaborative method, is one of the key difficulties in cognitive radio which has the potential to improve energy efficiency. The Energy-Efficient Scalable Routing Algorithm(EESRA) is used in this study which combines Low Energy Adaptive Clustering Hierarchy (LEACH) with an Energy-Efficient clustering and hierarchical routing algorithm. A novel machine learning approach is used in this paper to consider identical channels in Cognitive Radio Networks (CRN). When compared to LEACH, the EESRA algorithm extended the lifespan of network, resulting in the incorrect rate of .9895 and an error rate of 0.0105.
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