Delay-Optimal Channel Selection Method for Wireless Cognitive Networks
Driven by government policy and advanced front-end radio technologies, cognitive radio offers an ever-promising future in the next generation communication system. Due to the random characteristics of primary users, it is impossible to fully describe the activity feature in terms of time and space, rendering opportunity access unsafe to primary user. In order to minimize interference to primary users and find available channel as fast as possible, a history knowledge based algorithm is proposed in this work, which compound historical information with current observed information. Random early detection (RED) algorithm, which proves to be efficient in active queue management (AQM) for switching fabrics, is introduced to help select the desirable channel. In order to further suppress the collision probability, all the channels are sorted according to availability. Simulation results show that, compared with completely random spectrum selection method, the proposed RED-based channel access method gives better performance in terms of channel selection delay.