Multi-step spectrum occupancy prediction method based on association rule mining

Abstract

Radio spectrum occupancy prediction is a key technology in cognitive radio research. In the traditional method, only single step size prediction can be performed, and the effect of multi-step size prediction is significantly reduced. Referring to the idea of searching frequent item sets in Apriori algorithm，a multi-step spectrum occupation prediction method based on association rule mining is proposed. In terms of data acquisition, the electromagnetic spectrum detection system developed by the unit is used to monitor the frequency spectrum of FM broadcasting service(88~108 MHz) for 48 hours continuously, and some data whose occupancy meets the demand of spectrum occupancy prediction are selected for prediction and analysis. The experimental results show that the proposed method is effective in FM broadcasting frequency band, and the prediction accuracy of multi-step length is more than 70%. This paper also briefly analyzes the important parameters of the algorithm and points out the influence of the parameters on the accuracy of the output results.

Keywords

• cognitive radio
• spectrum monitoring
• spectrum prediction
• frequent pattern
• association rule mining