Efficient Spectrum Allocation Using Case-Based Reasoning and Collaborative Filtering Approaches

Cognitive radio environments utilize the scarce resource like spectrum efficiently through the dynamic spectrum access approach. Various models, including economic, game theory, genetic algorithms, and neural network models will become the catalysts to boost the dynamic spectrum access for efficient utilization of the spectrum. Combinations of these models may sometimes help better in allocation of unused spectrum (spectrum holes) for cognitive users (secondary users). In this paper, we introduced the case-base reasoning to identify a channel preferred by the secondary user. We then introduced automatic collaborative filtering for preference between two users which assigns the particular channel to the highest prioritized user. These two approaches were used along with the cooperative game concept to select the preferred channel for a cognitive user at any given time slot. The framework was designed using the CBR-ACF Algorithm and discussed using examples generated through simulations.