Optimizing Location of Edge Clouds with Baseband Units in Cloud Radio Access Network

Jackline Nakazibwe, J. Serugunda, R. Akol, Stephen S. Mwanje
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Abstract

Cloud radio access network architecture has become increasingly important in meeting the growing demand of high data rate services as well as managing interference among base station sites. However, this architecture is associated with high fronthaul link latencies that result into increased overall network latencies. This paper proposes a placement method for baseband units so as to lower the fronthaul link latencies. This is achieved by formulating the problem as a nonlinear optimization problem that is solved by fuzzy c-means clustering and a heuristic genetic based algorithm. The paper further investigates the user response time comparing it with the scenario before optimizing location of baseband units in edge clouds. Simulation results show that the proposed scheme greatly reduces overall fronthaul link latencies and cost of ownership in cloud radio access networks. We also show that there is an optimal number of edge clouds with baseband units for different cloud radio access network sizes. On the side of the users, the response time is greatly reduced when the baseband units are optimally placed.
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云无线接入网中基带单元边缘云位置优化
云无线接入网架构在满足日益增长的高数据速率业务需求以及管理基站站点之间的干扰方面变得越来越重要。然而,这种体系结构与高前传链路延迟相关联,从而导致整体网络延迟增加。为了降低前传链路的时延,提出了一种基带单元的放置方法。这是通过将问题表述为一个非线性优化问题来实现的,该问题由模糊c均值聚类和启发式遗传算法来解决。在优化基带单元在边缘云中的位置之前,进一步研究了用户响应时间,并将其与场景进行了比较。仿真结果表明,该方案大大降低了云无线接入网络的整体前传链路延迟和拥有成本。我们还表明,对于不同的云无线接入网络规模,存在带基带单元的边缘云的最佳数量。在用户方面,当基带单元被优化放置时,响应时间大大缩短。
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