How Local Information Improves Rendezvous in Cognitive Radio Networks

Cognitive Radio Network (CRN) is a promising technique for solving the wireless spectrum scarcity problem. Rendezvous is the fundamental process of CRNs. We aim at designing faster rendezvous algorithms for CRNs. We find that local information such as user's ID and the label of an available channel is very useful for designing faster rendezvous algorithms. First, we propose the Sequence-Rotating Rendezvous (SRR) algorithm. The SRR algorithm can guarantee rendezvous for any two users i and j in (2P²+ 2P) timeslots, where P is the least prime not less than the total number of channels in the network. Second, we utilize the user's identifier (ID) to design an ID-based Rendezvous (IDR) algorithm. The IDR algorithm can guarantee rendezvous for any two users i and j in (l + 1)(P_i + 2)(P_j + 2) timeslots, where Pi and Pj are the smallest primes which are not less than the numbers of available channels of users i and j respectively. Third, we propose a Channel-Label- based Rendezvous (CLR) algorithm which can guarantee rendezvous for any two usersin ((P_i+2) (P_j+2)+PN)(⌈log_2N⌉+1) timeslots, where N is the total number of channels in the network and P_N is the least prime which is not less than N. The theoretical Maximum Time To Rendezvous (MTTRs) of the three algorithms we propose are less than those of the state-of-the-art algorithms in the corresponding categories respectively in certain scenarios. All of our algorithms can be used in multi-user scenarios. We conduct a number of experiments to compare our algorithms with state- of-the-art rendezvous algorithms in different scenarios, the results of which confirm our theoretical analysis.