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 Terms— Cognitive Radio, Spectrum Sensing/Monitoring, Orothogonal Frequency Division Multiplexing (OFDM),
Energy Harvesting Algorithm, Quiet Period, Detection Probability.