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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, 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 GLRT algorithm. As a result, maximum-likelihood (ML) 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.

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