Spectrum Migration Scheme Based on Interval Mamdani Fuzzy Inference in Cognitive Radio Networks

The existing opportunistic spectrum access technologies can improve spectrum resource utilization significantly, but they still have some shortcomings in guaranteeing QoS of secondary users and effective utilization probability of spectrum resource in cognitive radio networks. In order to improve QoS of secondary users in cognitive radio networks, and promote the real performance of cognitive radio networks, a new concept named spectrum migration is introduced, and a novel spectrum migration scheme based on interval Mamdani fuzzy inference is put forward. In the spectrum migration scheme, unnecessary treated data and system load can be reduced by applying pre-decision method. In addition, spectrum occupation rate and link maintenance rate of licensed spectrum are comprehensively considered as spectrum migration factors. Then, spectrum migration degree can be calculated by fuzzy inference to guide secondary users to the optimal spectrum holes. To shorten inference time, interval Mamdani fuzzy inference is proposed based on Mamdani fuzzy inference, and the twice judgments are utilized to reduce the complexity of the spectrum migration process. Simulation results show that the scheme can decrease forced termination probability, service retransmission probability and spectrum migration times of secondary users' service transmission, maintain a higher system throughput and improve the effective utilization probability of cognitive radio networks spectrum resource at the same time.