Integration of propagation modelling assets for enhancing spectrum sensing capabilities in cognitive communication networking

Robust spectrum sensing and efficient cognitive communication networking (C²N) operation in various terrain environments require that the cognitive radio be proactive and dynamic in selecting the optimal sensing parameters for the current and future locations of mobile units. In spectrum sensing, the detector performance is characterized in terms of detection probability (the rate of C²N correctly sensing a busy channel and avoiding to use it), Pd and false alarm probability (the rate at which a free channel is mistakenly identified as busy), Pfa parameters. It is worth mentioning that providing higher detection probability should take precedence over providing lower false alarm rates, because a low Pd leads to harmful interference which, in turn, adversely affects other mobile devices whereas a high Pfa results in the C²N not using that specific channel.