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The success of advanced dynamic utilisation of the scarce spectrum in cognitive radio depends upon reliable primary signal detection where accurate noise power estimation plays a critical role. However, in practical scenarios, the noise power cannot be accurately estimated, which significantly degrades the performance of primary signal detection. To avoid inaccurate noise power estimation and associated accumulated problems. A novel two-stage Bayesian estimation-based energy detection algorithm is introduced here. This algorithm, as supported by simulation results, shows two main features: (a) a superior performance of 1 dB compared with previous methods; (b) the consistency of the algorithm has been proved indicating that 100 correct primary user signal detection can be approached as the number of samples tends to infinity.