Frequency-Domain Differential Energy Detection Based on Extreme Statistics for OFDM Source Sensing

This paper presents a novel differential energy detection scheme based on extremes of order statistics for sensing OFDM signals. The underlying initiative of this approach is applying the order statistics of the differential Energy Spectral Density in frequency domain. The proposed technique takes advantage of the channel selectivity which is inherited from high data-rate communications. The introduced frequency diversity allows this approach to meet FCC requirements even in low SNR environments i.e., (-25 ,-10) dB. Analytical results of sensing performance are provided in terms of both probability of false alarm and probability of detection. Furthermore, computer simulations show that the proposed technique outperforms two most commonly used source detection approaches namely conventional energy detection and cyclostationarity based detection for up to 10 dB gain in low SNR environments.