Large-scale Spectrum Measurement Study

Dynamic spectrum access has been a hot topic for extensive study in recent years. The increasing volumes 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 20MHz to 3GHz 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 2-dimensional frequent pattern mining algorithm that can predict channel availability based on past observations with considerable accuracy. Index Terms Spectrum Measurement, Channel Vacancy Duration, Service Congestion Rate, Spectrum Usage Prediction, Frequent Pattern Mining, FPM-2D, Spectral Correlation, Spatial Correlation