Novel Pilot-Assisted Spectrum Sensing for OFDM Systems by Exploiting Statistical Difference Between Subcarriers

This paper presents a novel pilot-assisted spectrum sensing technique for orthogonal frequency-division multiplexing (OFDM) systems. The main idea is based upon the physical nature that subcarriers carrying pilots or payload data have different first-order and second-order statistical properties. These differences vanish when the spectrum of interest is unoccupied. Therefore, the decision of spectrum availability can be formed based upon these differences, which can be explored through employment of frequency-domain differential operations. Thanks to the differential operations, the proposed technique has less sensitivity of the noise power uncertainty problem caused by imperfect hardware. Performance of the proposed technique is analytically formulated in terms of probability of false alarm (PFA) and probability of detection (PD). Computer simulations are carried out to elaborate the analytical results. It is shown that the second-order statistics based proposed technique outperforms the conventional pilot-assisted technique up to 7 dB. Moreover, it is shown that the first-order statistics based proposed technique outperforms the second-order statistics based proposed technique for small normalized Doppler shifts (≤ 0.013). However, the second-order statistics based proposed technique offers better performance for larger normalized Doppler shifts.