Spectrum sensing sequence prediction in cognitive radio networks  

作　　者：An Chunyan Ji Hong Si Pengbo Maoxu 

机构地区：[1]College of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, 100876, P.R.China [2]College of Electronics Information and Control Engineering, Beijing University of Technology, Beijing, 100876, P.R.China

出　　处：《High Technology Letters》2011年第4期371-376,共6页高技术通讯（英文版）

基　　金：Supported by the National Natural Science Foundation of China（No.60832009）, the Natural Science Foundation of Beijing （No.4102044） and the National Nature Science Foundation for Young Scholars of China （No.61001115）

摘　　要：Spectrum sensing is one of the key issues in cognitive radio networks. Most of previous work concenates on sensing the spectrum in a single spectrum band. In this paper, we propose a spectrum sensing sequence prediction scheme for cognitive radio networks with multiple spectrum bands to decrease the spectrum sensing time and increase the throughput of secondary users. The scheme is based on recent advances in computational learning theory, which has shown that prediction is synonymous with data compression. A Ziv-Lempel data compression algorithm is used to design our spectrum sensing sequence prediction scheme. The spectrum band usage history is used for the prediction in our proposed scheme. Simulation results show that the proposed scheme can reduce the average sensing time and improve the system throughput significantly.

关 键 词：spectrum sensing sequence prediction cognitive radio network Ziv-Lempel algorithm 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术] TN929.5[自动化与计算机技术—计算机科学与技术]