The knowledge of the statistical characterization of the primary user activity can make more efficient the spectrum selection techniques, which are a key technology to improve the Cognitive Radio (CR) systems performance. In order to provide this kind of primary user information, Radio Environment Maps (REM) data bases has been proposed. This paper presents a REM-based Real Time Testbed designed to validate and exploit the dynamicity of the REM data base to improve the performances of the Radio Resource Management (RRM) algorithms in the context of cognitive radio. The implemented testbed is a flexible HW/SW tool able to use spectrum measurements in licensed bands and validate the Cognitive Radio performance of the secondary users, without causing any interference on these primary users. In particular, the RRM strategy under study in the testbed envisages the optimization of the spectrum selection policy when secondary users, with different service profiles, access opportunistically a set of channels during the inactivity periods of primary users. The selection is done taking as input the statistical characterization of the primary user activity, which will be stored in the REM data base, and the secondary user service profiles.

Peer Reviewed