The data mining in wireless spectrum monitoring application
Fangwei Man, Rong Shi, Binbin He · 2017
With the rapid development of radio service and monitoring facilities, radio monitoring application steps into big data era. Big data analysis technology can help us get valuable information through dealing with massive monitoring data, which offer guidance to wireless spectrum resource management, abnormal signal detection, etc. In this paper, we adopt association rule mining algorithm to realize wireless spectrum occupancy prediction and achieve a satisfactory prediction accuracy, which has a certain significance for cognitive radio devices to apply dynamic spectrum access and improve spectrum utilization. After that, we present a survey about the use of distributed computing technology in radio monitoring. Finally, it concludes the problems worth studying in the future.