In this study, a new network architecture based on the software-defined networking (SDN) approach is proposed for cognitive radio networks (CRNs). The proposed network architecture [software-defined cognitive radio (SDCR)] assumes the responsibilities of network resource management for CRNs and provides a dynamic spectrum management mechanism with an SDN controller. In this way, the dependency of network users on base stations is reduced in dynamic cognitive radio environments, and network performance is improved by delegating some of the management responsibilities to the controller. The performance analysis of the SDCR is carried out through the RIVERBED MODELER simulation software. End-to-end delays and packet loss rates for the primary network are investigated by selecting different offered loads for secondary users. In addition, for the equal and different packet sizes, primary network and SDCR throughput are examined and network performance is improved by using channel bonding technique. The results indicate that the SDCR outperforms the traditional CRN architecture, in terms of the throughput, and the proposed architecture can provide effective performance. Bit error rate parameter is investigated in the study and the energy consumption parameter of the SDCR is also compared with the cognitive radio wireless network.

中文翻译：

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支持SDN的认知无线电网络架构

在这项研究中，针对认知无线电网络（CRN）提出了一种基于软件定义网络（SDN）方法的新网络架构。提出的网络体系结构[软件定义的认知无线电（SDCR）]承担CRN的网络资源管理职责，并提供带有SDN控制器的动态频谱管理机制。以此方式，在动态认知无线电环境中减少了网络用户对基站的依赖性，并且通过将一些管理职责委托给控制器来改善网络性能。SDCR的性能分析是通过RIVERBED MODELER仿真软件进行的。通过为辅助用户选择不同的负载，可以调查主要网络的端到端延迟和丢包率。此外，对于相同和不同的数据包大小，将检查主要网络和SDCR吞吐量，并使用信道绑定技术提高网络性能。结果表明，就吞吐量而言，SDCR优于传统的CRN体系结构，并且所提出的体系结构可以提供有效的性能。研究中研究了误码率参数，并将SDCR的能耗参数与认知无线电无线网络进行了比较。