关键词: BigBand算法, 欠采样, 噪声门限, 信号门限

Abstract: The BigBand algorithm is an under-sampling algorithm that uses the general sparseness of the signal.The traditional BigBand algorithm relies on experience to set a fixed threshold threshold.In the case of low signal-to-noise ratio and noise uncertainty,the value of noise is superimposed and amplified by spectrum aliasing,and the signal and noise are difficult to distinguish clearly,and the spectrum sensing ability is poor.Aiming at this problem,an improved BigBand algorithm based on adaptive threshold is proposed,the initial noise threshold and signal threshold are obtained by using the preset signal false alarm probability,and dynamically adjusts the threshold threshold according to the perceived environmental signal-to-noise ratio,and then selects noise or The signal threshold is used as the threshold threshold for signal judgment and perception.Experimental analysis shows that compared with the traditional BigBand algorithm,the improved algorithm can adapt to the environment with low signal-to-noise ratio and drastic noise changes,and has good anti-interference performance and better spectrum sensing capabilities.

Key words: BigBand algorithm, Under sampling, Noise threshold, Signal threshold