Competition-Based Channel Selection for Cognitive Radio Networks

In cognitive radio networks, unlicensed users need to learn from environmental changes. This is a process that can be done in a cooperative or non-cooperative manner. Due to the competition for channel utilization among unlicensed users, the non-cooperative approach may lead to overcrowding in the available channels. This paper is about a fuzzy-logic based decision making algorithm for competition-based channel selection. The underlying decision criterion integrates both the statistics of licensed users' channel occupancy and the competition level of unlicensed users. By using such an algorithm, the unlicensed user competitors can achieve an efficient sharing of the available channels. Simulation results are reported to demonstrate the performance and effectiveness of our suggested algorithm