Dynamic rendezvous algorithms for cognitive radio networks

Rendezvous is a fundamental process in constructing cognitive radio networks (CRNs), in which two users find a common channel for communication. The licensed spectrum is assumed to be divided into n non-overlapping channels and the users can sense the spectrum by equipping with cognitive radios. Most of previous works assume that the user can find a set of available channels (the channels not occupied by the licensed users) after spectrum sensing stage and the status of all channels are stable all the time. However, this assumption may not be true in reality and we focus on designing efficient algorithms when the status of the channels varies dynamically. In this paper, we introduce two models to describe the dynamic rendezvous problem. Denote pij as the probability that channel j is available for user i. In the Independent model, assuming all pij variables are independently distributed and we propose efficient algorithms for both synchronous and asynchronous users, which guarantee rendezvous in O (log2 n) and O (log3 n) time slots with high probability respectively. In the Dependent model, two nearby users have relevant available probabilities and we introduce a sensing phase and an attempting phase to guarantee rendezvous in O (ϵ log3 n log log log n) time slots with high probability, where ϵ is a small constant. We also present an algorithm to increase rendezvous load in the long run, which guarantee rendezvous for at least 1/4 of all time slots.