5G D2D通信的改进亲和传播聚类

Anusha Vaishnav, Amulya Ratna Swain, M. R. Lenka
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引用次数: 0

摘要

第五代移动网络(5G)是继4G网络之后的最新蜂窝技术。由于更多可用带宽和先进技术,5G网络的使用提高了数据速率。在其他几种技术中,设备到设备(D2D)通信是5G网络中用于高效数据传输的先进技术之一。D2D技术代表了两台设备之间的直接通信,无需基站的帮助。聚类算法是D2D通信中常用的处理动态设备的技术之一。聚类技术有助于将兴趣相似的用户分组并重构网络,从而在吞吐量、频谱效率、功耗、能耗等方面获得更好的性能。亲和性传播(Affinity Propagation, AP)聚类算法通过动态地准备簇和簇头来区别于其他聚类算法。然而,其他的聚类算法需要事先提供簇的数量和簇头信息。因此,本工作的重点是改进AP聚类算法,以便更好地准备簇和簇头,以提高D2D通信的效率。
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Improved Affinity Propagation Clustering for D2D Communication in 5G
Fifth-generation mobile network(5G) is the latest cellular technology after 4G networks. The Use of a 5G network enhances the data rate due to more available bandwidth and advanced technologies. Among several other technologies, Device-to-Device (D2D) communication is one of the advanced technologies used in 5G networks for efficient data transmission. D2D technology represents direct communication between two devices without the assistance of a base station. The clustering algorithm is one of the technologies used mostly in D2D communication to handle dynamic devices. The clustering technique helps to group users with similar interests and reconstruct the network to achieve better performance in terms of throughput, spectral efficiency, power, energy consumption, etc. The Affinity Propagation (AP) clustering algorithm has differentiated itself from the other clustering algorithms by dynamically preparing the clusters and cluster heads. However, the other clustering algorithms require the number of clusters and cluster head information beforehand. Hence, this work focuses on improving the AP clustering algorithm to prepare the clusters and cluster heads in a better way to enhance the efficiency of D2D communication.
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