A neighbour discovery approach for Cognitive Radio Network using Tower of Hanoi (toh) sequence based channel rendezvous

Abstract

Cognitive Radio Network (CRN) is a relatively new research area to improve spectral efficiency of wireless communication. Nowadays, the concept of commercial CRN (i.e., existence of primary and secondary users in licensed bands) is gaining popularity in wireless communication research. In fact, scarcity of bandwidth due to large number of wireless devices in different networks guides the unlicensed ISM (Industrial, Scientific and Medical) band to a saturation state. However, in CRN, at the absence of primary user, opportunistic medium access into licensed bands by the secondary users in different channels renders better bandwidth provisioning. The main concern and challenge for the CRN is channel rendezvous amongst the secondary users to discover the neighbours. A large number of existing works propose the channel rendezvous solutions using pseudo random channel hopping (i.e., switch from one channel to other) sequence. However, we argue that pseudo random sequence cannot provide efficient channel rendezvous in many scenarios and sometimes even the secondary users do not discover their neighbours. Hence, in this paper, we propose a channel hopping sequence method using the Tower of Hanoi (ToH) algorithm for multi-channel rendezvous amongst the secondary users of CRN. We have analysed and implemented the proposed mechanism, and found that it provides better results in terms of number of iteration and success rate for channel rendezvous than that of pseudo random approach.