ICSSSS: An intelligent channel selection scheme for cognitive radio ad hoc networks using a self organized map followed by simple segregation

In Cognitive Radio Ad Hoc Networks (CRAHNS), several spectrum bands with different channel characteristics may be available over a large frequency range. It is essential to identify the most appropriate spectrum band correctly which allow the Secondary Users (SUs) to exploit the band without disturbing the Primary Users (PUs). Many channel selection solutions, based on cooperative spectrum sensing, have been employed for this purpose depending on their prediction models for primary users' activities. In practice, cooperative spectrum sensing cannot completely solve the sensing problems which are false alarm and miss detection, especially in heavily shadowed or fading environment. This paper presents, ICSSSS, as an Intelligent Channel Selection Scheme for cognitive radio ad hoc network using Self organized map followed by simple Segregation. The contribution of the proposed scheme is twofold: using an unsupervised learnable Self Organizing Map (SOM) method to efficiently minimize the probability of the sensing errors (false alarm and miss detection), in addition to segregated channel selection strategy to speed up the search for the available best channel. Simulation results based on NS2 simulations show that the proposed scheme can be used with the advantage of better performance than other existing channel selection strategies.