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In order to increase spectrum utilization efficiency, CRs (Cognitive Radios) have been introduced to reuse white spaces left unused by legacy services under the strict constraint of not interfering them. In this context, this paper proposes to exploit the statistical characterization of Primary User (PU) activity to be retained in Radio Environment Maps (REMs) for spectrum selection purposes. The objective is to match multiservice secondary traffic to heterogeneous primary spectrum opportunities minimizing the SpHO (Spectrum HandOver) rate. Specifically focusing on dependence structures potentially exhibited by primary ON/OFF periods, two spectrum selection criteria have been first proposed to benchmark the utility of the embedded statistical patterns in the REM.
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