Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: 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. ,  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.  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 beten channels of the same service.  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.
['Sixing Yin', 'Dawei Chen', 'Qian Zhang', 'Mingyan Liu', 'Shufang Li']
I am writing a research paper on a idea Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study
[{"from": "human", "value": "I am writing a research paper on a idea Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: 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. ,  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.  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 beten channels of the same service.  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."}]