Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study
Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study
复制标题
DOI：
10.1145/1614320.1614323
复制
发表时间：
2009-09
影响因子：
7.9
通讯作者：
Dawei Chen;Sixing Yin;Qian Zhang;M. Liu;Shufang Li
中科院分区：
文献类型：
--
作者：
Dawei Chen;Sixing Yin;Qian Zhang;M. Liu;Shufang Li
近年来，动态频谱接入已成为广泛研究的主题。越来越多的文献需要更深入地了解当前频谱利用的特点。在本文中，我们提出了一项详细的频谱测量研究，数据在 20 MHz 至 3 GHz 频谱段内同时在中国广东省的四个地点收集。我们检查所收集数据的统计数据，包括信道空闲统计、每个无线服务内的信道利用率以及这些测量的频谱和空间相关性。主要发现包括信道空闲持续时间遵循指数分布，但不随时间独立分布，并且在同一服务的信道之间发现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一种 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。
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.