Cooperative Spectrum Sensing Scheme using Fuzzy Logic

In a communication system spectrum band has a crucial role. Spectrum band can efficiently use by cognitive radio because of its ability to sense surrounding environment. Cognitive radio sense vacant holes or unoccupied spectrum band by detecting the primary users' presence or absence in the spectrum. Also, prevent interference between signals. Using more than one cognitive radio in the detection process will increase the efficiency of spectrum usage. Conventional cooperative spectrum sensing detects signal for high SNR value but using machine learning techniques detection of signal occur under low SNR also increase efficiency and detection performance. The aim of is to classify signal and noise using Machine learning method for Cognitive Radio. Used machine learning technique for cooperative spectrum sensing method in cognitive radio based on the fuzzy membership functions and Fusion center (FC). At Fusion Center information combines from each the secondary users and using some fuzzy rules such as algebraic product, algebraic sum gives a final decision about the absence/presence of a primary user. Proposed System designed using multiple parameters. The Fuzzy Logic system gives much better results compared to the Referred system also Detection of signal occurs at low SNR condition.