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Spectrum anomaly detection is of great importance in wireless communicationto secure safety and improve spectrum efficiency. However, spectrum anomalydetection faces many difficulties, especially in unauthorized frequency bands.For example, the composition of unauthorized frequency bands is very complexand the abnormal usage patterns are unknown in prior. In this paper, a noiseattention method is proposed for unsupervised spectrum anomaly detection inunauthorized bands. First of all, we theoretically prove that the anomalies inunauthorized bands will raise the noise floor of spectrogram after VAEreconstruction. Then, we introduce a novel anomaly metric named as noiseattention score to more effectively capture spectrum anomaly. The effectivenessof the proposed method is experimentally verified in 2.4 GHz ISM band.Leveraging the noise attention score, the AUC metric of anomaly detection isincreased by 0.193. The proposed method is beneficial to reliably detectingabnormal spectrum while keeping low false alarm rate.

Noise Attention based Spectrum Anomaly Detection Method for Unauthorized Bands