Traditional spectrum sensing methods are susceptible to noise fluctuations and have poor detection accuracy under wireless communication conditions with low signal-to-noise ratio.The anti-noise performance and detection accuracy of traditional spectrum sensing methods can be effectively improved by combining the lifting wavelet denoising and dynamic threshold energy detection algorithm.First,perform odd and even sampling of the noisy signal,decompose the noise signal,remove the noise part,and reconstruct it into a new signal without noise,then use the energy detection method to count the energy accumulation of the signal,set the dynamic threshold,and finally use the dynamic threshold to determine whether the primary user signal exists.Lifting wavelet denoising can effectively remove the noise in the sampled signal and reduce the influence of noise on the detection accuracy of the energy detection method.The dynamic threshold can be adjusted according to noise fluctuations to adapt to the complex noise environment.The simulation results show that the lifting wavelet denoising combined with dynamic threshold energy detection algorithm has better detection accuracy than traditional spectrum sensing methods.This method improves its resistance to uncertain noise,enables it to adapt to complex communication environment,and also improves the reliability of spectrum sensing process.