Swarm Intelligence Based Dynamic Control Channel Assignment in Cogmesh

Abstract

In this paper we address the control channel assignment problem in a cognitive radio based wireless network, namely the CogMesh. Such a network is featured by the dynamic spectrum sharing of the secondary users coexisting with the primary users. The opportunistic nature of the spectrum utilization among the secondary users makes a global control channel infeasible. The self-coordination of the network, hence, becomes a challenge task. Considering the fact that common channels may temporarily exist among a local group of secondary users, we propose an adaptive approach that selects local common control channels independently by each secondary user according to the qualities of the detected spectrum holes and the choices of its neighbors. To achieve this, a swarm intelligence-based algorithm is used to facilitate the common control channel selection. The idea is to use HELLO messages periodically broadcasted by neighbors as the pheromone to rank the common channels so as to expedite the channel selection process. The algorithm is completely distributed and therefore scalable. Moreover, it is simple, flexible, adaptive, and well balanced on the exploitation and exploration of the radio resources. The behaviors and performance of the proposed algorithm are verified by simulation.