Spectrum Sensing Using Energy Harvesting Algorithm For Cognitive Radio Networks

Spectrum Sensing is the key challenge for Cognitive Radio Networks that allows the detection of primary user reappearance during secondary user transmission. The proposed Energy Harvesting Algorithm will detect the reappearance by sensing the change in the signal strength over a number of reserved tones in OFDM frame and this method also reduce the detection time of secondary receiver and decreases the frequency for spectrum sensing. The performance of Energy Harvesting Algorithm was evaluated by finding two parameters Probability of Detection and Probability of False Alarm and in presence of varying Secondary to Primary Power Ratio (SPR). Simulation result shows that probability of detection increases with increase in probability of false alarm. This method also gives high performance with reduces complexity compared to traditional methods. This algorithm also reduces complexity and comparison is done between energy harvesting algorithm and receiver statistic show that our algorithm shows enhanced performance for detection. These results are verified by MATLAB. Index Termsâ€” Cognitive Radio, Spectrum Sensing/Monitoring, Orothogonal Frequency Division Multiplexing (OFDM), Energy Harvesting Algorithm, Quiet Period, Detection Probability