基于电磁环境数据的信息挖掘与关联分析

Information mining and association analysis based on electromagnetic environment data

城市通信技术的改革换代和用频设备的逐渐增多使得电磁环境变得越来越复杂。充分了解频谱资源利用的特性是提高频谱管理效率的关键。为了更全面地探索频谱利用的特点,提出一套完整的对复杂多样电磁环境大数据进行详细数据质量分析和处理的流程,分别对处于同一服务的不同信道、处于不同服务的不同信道进行频谱相关性分析,证明了频谱之间的相关性;对电磁环境大数据进行属性构造,构造了频率维占用度和时间维占用度属性。引入图像处理领域的多维混合高斯模型,对电磁信号进行背景噪声的去除,提取电磁信号,为后续的信息挖掘和关联分析奠定基础。

With the development of urban communication technology and the increase of frequency equipment, the electromagnetic environment becomes more and more complex. Fully understanding the characteristics of spectrum resource utilization in the past is the key to improve the efficiency of spectrum management. A complete process about detailed data quality analysis for big data in complex and diverse electromagnetic environment is proposed, in order to explore the characteristics of spectrum utilization more comprehensively. The spectrum correlation for different channels in the same service, and for different channels in different services, is performed. Attribute construction is carried out for big data of electromagnetic environment, including the attributes of frequency dimension occupancy and time dimension occupancy. The multi-dimensional Gaussian mixture model in the field of image processing is introduced to remove the background noise of the electromagnetic signal and extract the electromagnetic signal, which can lay the foundation for the subsequent information mining and association analysis.