Effective Channel Detection at Low SNR in Cognitive Radio Network Using Matched Filter Approach and Compare with Energy Detection - based Approach

Abstract

Aim: The study aims to detect the effective channel in cognitive radio network at low SNR using an innovative algorithm based on matched filter detection and compared it with energy detection. Materials and methods: The spectrum sensing based on novel matched filter detection with 10 samples is compared with the energy detection by varying the SNR conditions, using MATLAB. Results: The probability of detection of the matched filter is high at low SNR(-30db) then compared to the probability of detection of energy detection at low SNR(-10db) and the significance level is 0.002, i.e., (P<0.05) which gives better sensing performance. Conclusion: this would be proved to conclude that at low SNR conditions the matched filter detection gives significantly high sensing probability.