Fuzzy Logic Based Spectrum Sensing for Cognitive Radio Networks

It is inevitable for cognitive radio to find unutilized portion of the spectrum more accurately for successful deployment of dynamic spectrum sensing. To achieve highly reliable spectrum sensing, usually cooperative spectrum sensing is employed but still there is a margin to improve local sensing decisions. Cooperative spectrum sensing improves reliability of sensing at the cost of cooperation overhead among cognitive radio users, which can be reduced by improving local spectrum sensing. Several signal processing techniques for primary user detection have been proposed in literature but still there is room for researchers in this field to explore more sophisticated approaches to enhance sensing efficiency. This paper proposes a two stage local spectrum sensing approach. In first step, each cognitive radio perform existing spectrum sensing techniques i.e. energy detection, matched filter detection and cyclostationary detection. While in second stage, the output from each technique employed in step 1 is combined using fuzzy logic to ultimately decide about the presence or absence of primary user. The proposed approach shows significant improvement in sensing accuracy by exhibiting higher probability of detection and low false alarms.