Channel-Grouping based rendezvous algorithm for cognitive radio adhoc networks

Abstract

Cognitive Radio is utilized to exploit the existing wireless spectrum opportunistically, in which way to alleviate the spectrum shortage problem. It is of fundamental importance in cognitive radio adhoc networks for users to meet on a common channel via rendezvous and thereby establish communication links. In this paper, we investigate the probability analytic model to discuss the problem of rendezvous. Furthermore, a resulting Channel-Grouping based algorithm is proposed for decentralized rendezvous. The basic idea of the algorithm is to divide all channels into small sets, reducing the number of selectable channels in each round and thus improving the probability of successful rendezvous. Extensive simulations show that our proposed algorithm outperforms the other rendezvous schemes.