Spectrum Migration Approach Based on Pre-decision Aid and Interval Mamdani Fuzzy Inference in Cognitive Radio Networks

Abstract

This study intends to improve the QoS of SUs and CRNs performance. A novel spectrum migration approach based on pre-decision aid and interval Mamdani fuzzy inference is presented. we first define spectrum migration factors as spectrum characteristic metrics for spectrum migration decision. In addition, we use predecision aid to reduce system complexity and improve spectrum migration efficiency. To shorten spectrum migration decision time and seek the optimal spectrum holes, interval Mamdani fuzzy inference is put forward. Finally, simulation results show the proposed approach can inhibit the upward trend of service retransmission probability and average migration times effectively, and improve the effective utilization of CRNs spectrum resource significantly.

Interval Certitude Rule Base Inference Method using the Evidential Reasoning

“…Many methods have been proposed for showing uncertain knowledge and information. Such as the certainty factor based inference method [36], inference method using the Dempster-Shafer theory [12], Belief Rule Base Inference Methodology using the Evidential Reasoning (RIMER) [31,[38][39][40], subjective Bays method [36], fuzzy inference method [29], et al…”