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Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study

机译:挖掘频谱使用数据:大规模频谱测量研究

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Dynamic spectrum access has been a subject of extensive study in recent years. The increasing volume of literatures calls for a deeper understanding of the characteristics of current spectrum utilization. In this paper, we present a detailed spectrum measurement study, with data collected in the 20 MHz to 3 GHz spectrum band and at four locations concurrently in Guangdong province of China. We examine the statistics of the collected data, including channel vacancy statistics, channel utilization within each individual wireless service, and the spectral and spatial correlation of these measures. Main findings include that the channel vacancy durations follow an exponential-like distribution, but are not independently distributed over time, and that significant spectral and spatial correlations are found between channels of the same service. We then exploit such spectrum correlation to develop a 2D frequent pattern mining algorithm that can predict channel availability based on past observations with considerable accuracy.
机译:近年来,动态频谱访问已成为广泛研究的主题。越来越多的文献要求对当前频谱利用的特征有更深入的了解。在本文中,我们将进行详细的频谱测量研究,收集在20 MHz至3 GHz频带中同时在中国广东省四个地点收集到的数据。我们检查收集到的数据的统计信息,包括信道空缺统计信息,每个单个无线服务内的信道利用率以及这些度量的频谱和空间相关性。主要发现包括,信道空置持续时间遵循指数状分布,但并非随时间独立分布,并且在相同服务的信道之间发现了显着的频谱和空间相关性。然后,我们利用这种频谱相关性来开发2D频繁模式挖掘算法,该算法可以根据过去的观察结果以相当高的精度预测信道可用性。

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