A Suboptimal Sensing Scheme for OFDM Signal Based on Pilots Estimation in Cognitive Radios

The optimal detector for CP (Cyclic Prefix)-OFDM (Orthogonal Frequency Division Multiplexing) signal with inherent periodic pilots in low signal to noise ratio environments relies on perfect time synchronization. In this paper, we modify the optimal detector and propose a new suboptimal sensing scheme based on pilots estimation (SSS-BPE). In the proposed SSS-BPE, the likelihood criterion and periodicity of the pilot components are utilized to estimate the pilots. The estimated pilots together with the modified optimal sensing scheme are then utilized to detect the primary user signal based on the Neyman-Pearson Criterion. The proposed SSS-BPE efficiently exploits typical features in the CP-OFDM signal with no requirement on time synchronization information, and is able to distinguish between the primary user signal and interference. Theoretical analysis and simulation results show that the proposed scheme can effectively and reliably detect the presence of spectrum bands that are not used by the primary users. Furthermore, the computational complexity of the proposed SSS-BPE is relatively low compared to the counterparts.