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Short Survey on Clustering Techniques for RRH in 5G networks

机译:5G网络中RRH群集技术的简短调查

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Cloud Radio Access Network (C-RAN) is a promising solution to meet the 5GGP requirements for 5G Networks. The C-RAN is based on the idea of splitting the conventional eNB into two parts: the Remote Radio Head (RRH) and the Base Band Unit (BBU). The RRH will be responsible for the RF transmission and it will be densified to enhance the capacity of the network and the quality of service in response to the ever-increasing high demand for the applications. The BBU will care about the computational processing. To reduce the installation and maintenance costs and to enable and improve advanced features of the network such as Coordinated Multi-Point (CoMP) and enhanced Inter-Cell Interference Coordination (e-ICIC), the RRHs should be pooled and grouped into clusters. Several RRHs will be assigned to one BBU which will break with the conventional one-to-one mapping. The Clustering task is considered to be an NP-Hard problem. This article surveys the literature on Clustering algorithms and techniques as they apply to C-RAN Architecture and evaluate the resulting configuration of BBU pools.
机译:云无线电接入网络(C-RAN)是一种有前途的解决方案,可以满足5G网络的5GGP要求。 C-RAN基于将常规eNB分为两部分的想法:远程无线头(RRH)和基带单元(BBU)。 RRH将负责RF传输,并且将对RRH进行密集化,以增强网络的容量和服务质量,以应对不断增长的应用需求。 BBU将关心计算处理。为了减少安装和维护成本,并启用和改进网络的高级功能(例如,协作多点(CoMP)和增强的小区间干扰协调(e-ICIC)),应将RRH合并并分组到群集中。几个RRH将分配给一个BBU,这将与常规的一对一映射关系破裂。聚类任务被认为是NP-Hard问题。本文研究了适用于C-RAN体系结构的群集算法和技术的文献,并评估了BBU池的最终配置。

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