摘要
在电视空白频谱检测的研究中,现有的检测方法无法有效地区分无线麦克风信号和窄带干扰,从而导致很高的误警率,使得可用空白电视频段的数目急剧下降.为了解决这个难题,提出了一种基于周期图的无线麦克风信号检测方法.该方法通过周期图法来估计信号的功率谱密度,利用窄带干扰的功率谱呈现为一根线谱,而无线麦克风信号的功率谱相比于窄带干扰有细微展宽的特征来区分二者.同时,该方法建立了针对高斯向量的单边判决检测器模型,该模型把KL距离作为检验统计量.仿真和实验结果均表明,该方法能有效地检测出电视空白频谱中的无线麦克风信号.
In the study of TV white space （TVWS） spectrum sensing, the existing detection methods are unable to effectively distinguish between a wireless microphone signal and narrowband interference, which leads to a high false alarm rate and thus severely reduces the amount of sensed TVWS spectrum. In order to solve this problem, a periodogram-based sensing approach for wireless microphone signal was proposed. The approach focused on the periodogram as an estimate of the power spectral density （PSD）, utilizing the property that narrowband interference has a line spectral component while a wireless microphone signal has a slightly dispersed PSD. In addition, the approach formulated the resulting decision model as a one-sided test for Gaussian vectors, based on Kullback-Leibler （KL） distance type of decision statistics. Both the simulation and experimental validation results indicate that the proposed approach is a promising solution for sensing wireless microphones in TVWS.
基金
国家自然科学基金(61071095)
中科院百人计划资助
