Dynamic Control Channel Assignment in Cognitive Radio Networks Using Swarm Intelligence

In recent years, a variety of algorithms for cognitive radio networks have been proposed. Many of these algorithms rely on the exchange of control information among the cognitive radio nodes and often require the presence of a globally available control channel. This requirement however poses a problem in a practical deployment: First, due to spectrum fluctuations such common control channel may be unknown at deployment stage. Second, when designating a fixed, dedicated control channel (for example in licensed spectrum), this will increase costs and expose vulnerability to the operation of the cognitive radio network. Thus, to overcome this difficulty, control channels should be dynamically assigned and managed in cognitive radio networks. In this paper, we propose the use of swarm intelligence as a way to dynamically find and manage such control channels in cognitive radio networks. The system we describe is able to independently identify viable control channels and adapt in presence of changing spectrum. We formalize the problem of control channel assignments to the multi-commodity flow problem, measure the performance of our approach in a hardware implementation and software simulation and compare the results against the theoretically optimal solution.