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Proposed by Joseph Mitola III in 1999, Cognitive Radio (CR) has been considered as a promising solution for intelligent and efficient utilization of scarce spectrum in the communication world. CR brings about flexibility and self-adaptability to networks, by deploying most of functions on software. As the future communication era enables efficient utilization of radio resource, shrewd management of network elements, and dynamic adjustment to the environment, CR will surely play an influential role. This paper depicts a reconfigurable approach for end-to-end performance evaluation in Cognitive Radio Networks (CRNs). Based on Progressive Theory (PT) that derives from Complex Network Theory (CNT), the proposed approach caters for an extensive content of reconfigurability and performance-complexity tradeoff. The reconfigurable method explores the end-to-end performance in a rigorous manner, and takes all the Network Elements (NEs) of end-to-end transmission links into account. In addition, an end-to-end performance engine depending on cognitive cycle and classification tactic is demonstrated in detail. The classification tactic grades the evaluation factors in a novel way with a range of diversity sets. At last, a concise conclusion is put forward.