The field of telecommunication has undergone a very rapid technological evolution, which has forced researchers to find techniques that allow better exploitation of hardware and software. Among the proposed technologies, cognitive radio, a concept that was designed after several technologies such as software radio. Cognitive radio has been widely used for opportunistic access of the shared spectrum and has defined the cognitive nodes by their ability to intelligently adapt the environment to achieve specific objectives through advanced techniques. In this context, clustering techniques were adopted in cognitive radio networks (CRNs) due to their great advantages especially for routing. In this article, we propose a parallel mode of the k‐NN algorithm. The aim is to make a fast assignment of radio nodes in CRNs organized in the form of clusters. The obtained results are very satisfactory because we have been able to reduce to about 50% the execution time of the basic algorithm (sequential).

中文翻译：

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基于并行计算的认知无线电网络中一种新的快速k近邻分类算法

电信领域经历了非常迅速的技术发展，这迫使研究人员寻找可以更好地利用硬件和软件的技术。在提议的技术中，认知无线电是一种概念，它是根据多种技术（例如软件无线电）而设计的。认知无线电已广泛用于共享频谱的机会性访问，并通过它们智能地适应环境以通过先进技术实现特定目标的能力来定义认知节点。在这种情况下，由于认知无线电网络（CRN）的巨大优势，尤其是在路由选择方面，集群技术被采用。在本文中，我们提出了k-NN算法的并行模式。目的是在以群集形式组织的CRN中快速分配无线节点。