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Neuro-fuzzy based two-stage spectrum allocation scheme to ensure spectrum efficiency in CRN–CSS assisted by spectrum agent

机译:基于神经模糊的两阶段频谱分配方案,以在频谱代理协助下确保CRN–CSS中的频谱效率

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摘要

Cognitive radio network (CRN) is a promising technology to solve increasing spectrum scarcity problems in recent times. This study resolves the problem of cooperative spectrum sensing (CSS) and spectrum allocation in CRN-CSS in order to improve spectrum efficiency. A two-stage spectrum allocation scheme is initiated by grouping secondary users (SUs) with the knowledge of one-hop neighbor approach, which leads to minimised grouping time. These grouped SUs perform spectrum sensing in cooperative manner. Optimal channel assignment (OCA) process assigns channels to each SU in a group in a dynamic manner. Upon the assigned channel, SU performs spectrum sensing with the aid of the enhanced threshold energy detection (ETED) method. Finally, the available spectrum is allocated to SUs by a novel two-stage allocation approach. In this approach, SUs, which provide accurate spectrum sensing result, are given high priority for spectrum allocation. These SUs are detected through global decision making at the fusion centre (FC). A novel mining tree scheme with a spectrum agent is adopted for decision making at the FC. The neuro-fuzzy based spectrum allocation scheme in two-stage allocation supports effective spectrum allocation. An extensive experimental result exhibits promising improvements than in the previous approaches.
机译:认知无线电网络(CRN)是解决近来日益严重的频谱稀缺问题的有前途的技术。这项研究解决了CRN-CSS中的协作频谱感知(CSS)和频谱分配问题,以提高频谱效率。通过对二级用户(SU)进行分组并了解一跳邻居方法,可以启动两阶段的频谱分配方案,从而将分组时间降至最低。这些分组的SU以协作方式执行频谱感测。最佳信道分配(OCA)过程以动态方式将信道分配给组中的每个SU。在分配的信道上,SU借助增强的阈值能量检测(ETED)方法执行频谱感测。最后,可用频谱通过新颖的两阶段分配方法分配给SU。在这种方法中,可以将提供准确频谱感测结果的SU分配给频谱分配高优先级。这些SU是通过融合中心(FC)的全局决策检测到的。在FC上,采用具有频谱代理的新型挖掘树方案进行决策。两阶段分配中基于神经模糊的频谱分配方案支持有效的频谱分配。广泛的实验结果显示出比以前的方法更有希望的改进。

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