Adaptive Rendezvous for Heterogeneous Channel Environments in Cognitive Radio Networks

Rendezvous is the fundamental challenge in cognitive radio networks to find each other on a specific channel and establish a communication link. The primary focus of this paper is to design an algorithm for blind rendezvous, i.e., a rendezvous without a coordinator or common control channel. Channels to jump are assumed to be homogeneous in prior work; however, in the real world, channels exhibit different conditions. Therefore, we propose an adaptive jumping pattern such that a superior channel is considered more frequently based on its noise level and users have a greater possibility to rendezvous on such a channel. Furthermore, in this paper, we investigate the rendezvous problem with multiple radio interfaces. When multiple radio interfaces are available for users, the possibility of rendezvous increases; however, the number of channels to jump for each interface may not be the same as other users' interfaces. We propose an adaptive rendezvous algorithm that can function for multiple interfaces and different sizes of channel lists and an adaptive jumping pattern for different channel conditions. We prove that the proposed algorithm provides guaranteed rendezvous and derive the maximum time-to-rendezvous (TTR), which is also verified via simulation results. Further, our algorithm outperforms jump-and-stay in terms of TTR while enabling users to rendezvous on a better channel.