Exploiting Historical Spectrum Occupancy Information for Adaptive Spectrum Sensing

At present wireless devices are able to select their working frequency only to a limited extend although several measurements have shown that the current spectrum regulations are inefficient. Dynamic spectrum access is seen as a promising approach that might solve this inefficiency. Spectrum sensing is one of the main tasks involved. We compare in this paper four methods to efficiently sense the current spectrum based on the spectrum occupancy information statistics. The parameters of all methods are extracted from spectrum occupancy data gathered during an extensive measurement campaign. We show that the usage of historical information considerably improves the spectrum sensing process. We also show that the modelling of the periodic behaviour of the licensed signals leads to negligible performance enhancements because only very few periods shorter than several minutes can be found within 20 MHz-6 GHz.