电讯技术2016，Vol.56Issue(11)：1183-1188,6.DOI:10.3969/j.issn.1001-893x.2016.11.001
基于关联规则挖掘的无线电频谱占用预测
Wireless Spectrum Occupancy Prediction Based on Association Rule Mining
摘要
Abstract
Wireless spectrum occupancy prediction is one of the key technologies in cognitive radio sys-tems. A 24-hour spectrum measurement experiment is conducted in the uplink bands of GSM service( ran-ging from 890 MHz to 915 MHz ) and the partial broadcasting services ( ranging from 750 MHz to 806 MHz) ,in Chengdu,Sichuan Province. For a large scale of history data produced by radio monitoring sys-tems, association rules mining method in partial periodic pattern is chosen to mine frequent patterns in spectrum usage which can be used for generating association rules and acquiring using patterns of specific spectrum,thus realizing wireless spectrum occupancy prediction. The experiment results prove that the method can achieve a satisfactory prediction accuracy in two service bands(74. 02% and 83. 98% respec-tively ) . Moreover,the experiment points out sensitive parameters of this algorithm and offers a brief analysis of the parameters. The research has a certain significance for cognitive radio devices to apply dynamic spec-trum access technology and improving spectrum utilization.关键词
认知无线电/无线电监测/频谱预测/关联规则挖掘/部分周期模式Key words
cognitive radio/radio monitoring/spectrum prediction/association rule mining/partial periodic pattern分类
信息技术与安全科学引用本文复制引用
满方微,石荣,何彬彬..基于关联规则挖掘的无线电频谱占用预测[J].电讯技术,2016,56(11):1183-1188,6.基金项目
电子信息控制重点实验室基金项目(JS15120401535) Foundation Item:Foundation of Science and Technology on Electronic Information Control Laboratory(JS15120401535) （JS15120401535）
