Autoregressive Spectrum Hole Prediction Model for Cognitive Radio Systems

Author

Wen, Zhigang ; Luo, Tao ; Xiang, Weidong ; Majhi, Sudhan ; Ma, Yunhong

Author_Institution

Sch. of Telecommun. Eng., Beijing Univ., Beijing

fYear

2008

Firstpage

154

Lastpage

157

Abstract

In this paper, an autoregressive channel prediction model is presented for cognitive radio(CR) systems to estimate spectrum holes. This model adopts a second-order autoregressive process and a Kalman filter. A Bayes risk criterion for spectrum hole detection is presented by considering interference temperature and channel idle probability. Theoretical analysis and simulations show that CR systems based on this scheme can greatly reduce the number of collisions between licensed users and rental users.

Keywords

Bayes methods; Kalman filters; cognitive radio; wireless channels; Bayes risk criterion; Kalman filter; autoregressive channel prediction model; autoregressive spectrum hole prediction model; channel idle probability; cognitive radio systems; interference temperature; second-order autoregressive process; spectrum hole detection; Autoregressive processes; Chromium; Cognitive radio; Communications Society; Conferences; Fading; Interference; Predictive models; Temperature distribution; USA Councils;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications Workshops, 2008. ICC Workshops '08. IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-2052-0

Electronic_ISBN

978-1-4244-2052-0

Type

conf

DOI

10.1109/ICCW.2008.34

Filename

4531882