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Adaptive IED Spectrum Sensing Algorithm for Different Duty Cycle Values

The Energy Detection (ED) represents the most used and the simplest solution for implementing spectrum sensing in Cognitive Radio (CR) systems. Previously, an Improved ED (IED) algorithm was proposed, which estimates the average energy over more consecutive sensing slots. We propose an Adaptive threshold IED (AIED) algorithm, which requires some a priori knowledge about the Primary User (PU) signal, such as its average duty cycle and Signal-to-Noise Ratio (SNR). We compared the performance of the AIED algorithm with the Adaptive Classical ED (ACED) algorithm for different SNR and duty cycle values. For the same decision error probability, we demonstrate a detection SNR gain of more than 1 dB of AIED over ACED, in the low SNR regime, for high duty cycle values.