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A Network Calculus Analysis for the Baseband Processing Capacity in Cloud Radio Access Network

机译:云无线电接入网络基带处理能力的网络微积分分析

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Recently, cloud radio access network (C-RAN) has been widely regarded as a promising architecture for the next generation cellular networks. By separating traditional cellular base station to remote radio head (RRH) and baseband unit (BBU), C-RAN exhibits many advantages such as lower operating expenditure, higher throughput and energy efficiency. In order to understand the potential of C-RAN, much effort has been devoted to analyzing the performance of C-RAN. However, we notice that existing work usually assumes some preknown stochastic characteristics on the distribution of network traffic demands. In this paper, we would like to derive the backlog conditions in the BBU pool so as to understand how C-RAN can satisfy the real-time requirement in general cases without relying on any stochastic assumption. Specially, we build an analysis framework based on network calculus to analyze the baseband processing capacity of BBU pool in C-RAN. Then, we derive the effective bandwidth, based on the aggregated flow from RRHs, as the upper bound of the processing capacity of BBU pool. With the derived effective bandwidth, the upper bound of the number of BBUs can be also obtained accordingly. Numerical results validate the analysis result.
机译:最近,云无线电接入网络(C-RAN)被广泛认为是下一代蜂窝网络的有希望的架构。通过将传统的蜂窝基站分离到远程无线电头(RRH)和基带单元(BBU),C-RAN表现出许多优点,例如较低的操作支出,较高的产量和能量效率。为了了解C-RAN的潜力,很多努力都致力于分析C-RAN的性能。但是,我们注意到现有的工作通常假设有关网络交通需求分配的一些预指导随机特征。在本文中,我们希望在BBU池中获得积压条件,以了解C-RAN在一般情况下如何满足实时要求,而无需依赖任何随机假设。特别是,我们构建基于网络微积分的分析框架,分析C-RAN中BBU池的基带处理能力。然后,我们基于来自RRH的聚合流量的汇总流量来得出有效带宽,作为BBU池处理能力的上限。利用导出的有效带宽,也可以相应地获得BBU的数量的上限。数值结果验证了分析结果。

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