Simple solutions may still be best: on the selection of working channels in a channel-hopping cognitive network

Spectrum decision – i.e., the selection of a channel for the next hop – is one of the most important factors that affect the performance of a channel-hopping cognitive network. In this paper, we compare the performance of a number of channel selection algorithms through the probability of collisions with primary user transmissions. The results indicate that a simple histogram-based selection algorithm performs the best, except in the somewhat unrealistic scenario where primary users are homogeneous with respect to mean period and mean duty cycle of their channel activity, in which case selecting the next-hop channel among those that have most recently turned idle offers the best performance. Furthermore, histogram-based selection is shown to be quite resilient to errors inherent to channel sensing, and is thus a primary candidate for a wide range of applications of channel-hopping cognitive networks. Copyright c ⃝ 0000 John Wiley & Sons, Ltd.