Low-Complexity Energy Detection for Spectrum Sensing With Random Arrivals of Primary Users
Due to random arrivals of primary-user signals, the timing misalignment issue should be considered for spectrum sensing in cognitive radio (CR) systems, such as CR-based femtocell networks. To deal with this issue, two approaches were recommended in the literature, including Bayesian and generalized likelihood ratio test (GLRT) detectors. However, the Bayesian test requires perfect knowledge of the distribution of unknown parameters. Therefore, it is impractical due to its implementation complexity. To design a low-complexity energy detector (ED), this work proposes an ED scheme based on the GLRT algorithm. As a result, maximum-likelihood estimation for the timing misalignment is devised, and the performance of the proposed scheme is analyzed. The results show that the proposed GLRT detector features a low-complexity and satisfactory performance.