Number of channels adjustment for cognitive radio networks

Abstract

Cognitive radio networks (CRNs) are considered as a promising approach to enhance the spectrum utilization for large-scale Internet of Things (IoTs). In a CRN, two secondary users (SU nodes) must have a rendezvous before they can communicate with each other. Applying channel hopping is widely adopted to achieve rendezvous between any pair of users. In most of the existing channel hopping protocols, SU nodes switch among all the available channels. Because time to rendezvous (TTR) is in general proportional to the number of channels being used, these channel hopping protocols suffer from long TTR. When the number of SU nodes in the network is not large, using a small portion of the whole available channels may help reduce TTR. A fundamental problem to realize such an idea is to determine the number of channels to be used given the number of SU nodes in a CRN. In this paper, we define the optimal number of channels problem. To the best of our knowledge, it is the first work to theoretically handle the optimal number of channels problem. The proposed dynamic number of channel adjustment scheme (DNCA) operates on top of existing channel hopping protocols and can enhance the performance of them. Simulation results verify the improvement of DNCA when applied to existing channel hopping protocols, Jump-Stay and E-AHW.