A Hybrid Intelligence-Based Cognitive Engine

Demand for a reliable and adaptive intelligence generalization system has become an essential task to both the WCS's developers and its numerous services providers. Since WCS's spectrum is naturally known to be unstable, time-dependent and currently not only scarce in capacity but heavily congested and the impacts of its various services and its rapidly evolving applications are constantly making the system to be extremely complex. However as proposed by Mitola in 1999, Cognitive Radio (CR) has been developed with such intelligence capabilities and through it, the present-day WCS's spectrum complexity can be effectively managed, at the same time increases its scarce and the highly varying spectrum utilization particularly in complicated WCS's environments. To address this, CR system through its intelligence mechanism, which is also known as the Cognitive Engine (CE) enforces such adaptive intelligence functionalities to dynamically adjust its input parameters, observing its surrounding environment and ultimately makes its decision to meet the WCS's desired objective. This paper proposes the hybridization of two different Artificial Intelligence systems to design and implement an adaptive intelligence system for CR systems to predict the WCS's required objective.