Second-Order Statistical Techniques for Enhancing Spectrum Sensing in Cognitive Radio

This study explores the use of cognitive radio as a solution to the problem of radio spectrum scarcity and ineffectiveness. The focus is on spectrum sensing, a critical aspect of cognitive radio with various algorithms. The research examines a spectrum sensing algorithm based on the cyclic prefix correlation coefficient in OFDM signals(Orthogonal Frequency Division Multiplexing). The detection threshold is determined using a constant false alarm rate and a method for minimizing the average total error probability. Additionally, a formula for normalized spectrum utilization for primary and secondary users is presented. The results of the simulation show improved performance of the detector through the use of an adaptive threshold, resulting in a 6 dB increase in the probability of detection at 0.6 compared to a fixed threshold. The normalized spectrum utilization improved by approximately 5% at SNR = -12 dB for a spectrum occupancy of 0.5 and by 25% at SNR = -20dB for a spectrum occupancy of 0.7.