Local Independent Control of Cognitive Radio Networks

Many different algorithms for managing cognitive radio networks have been proposed. While these algorithms have applied the whole range from centrally managed to distributed control schemes, a common feature of previous work is the reliance on explicit communication to exchange and negotiate configuration information. This paper describes a new class of cognitive radio control algorithms employing local independent control based upon swarming behavior found in nature. We examine the feasibility of such local independent control in a testbed implementation of the algorithm, configuring and dynamically adapting a cognitive radio network. We find that approach is suited to coordinate a cognitive radio network based on passive observation of its environment only and may coordinate with other control algorithms deployed in heterogeneous secondary user networks.