随机C-RAN中前传和虚拟基站的经济有效联合建立

Yunyi Wu, Yongbing Zhang
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引用次数: 0

摘要

云无线接入网(CRAN)通过在终端用户附近定位远程无线电头(RRHs)并将与RRHs相对应的基带单元(BBUs)集中在中心云中,为移动终端用户提供低延迟和高速服务。但是,考虑到时变的业务负载,需要一种能够响应不断变化的业务负载以满足用户需求的自调节基站。本文的研究重点是在形成一个自调节的虚拟BS (VBS)时,最大限度地降低前传的建立成本和带宽消耗。由于前传是连接bbu和RRHs的CRAN的关键基础设施,影响VBS的形成,但不能动态调整,我们共同考虑它们的决策,并将其描述为一个两阶段随机问题。由于该问题可以线性化为整数线性规划(ILP),但在网络规模较大的情况下难以求解,我们提出了一种受Benders分解(BD)启发的FEBD方法来实现最优前传连接。此外,我们提出了一种启发式方法,可以根据用户需求快速调整VBS的形成。数值实验表明,将FEBD与启发式方法结合使用,计算时间明显缩短,结果与ILP结果接近。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cost-Effective Joint Establishment of Fronthaul and Virtual Base Stations in a Stochastic C-RAN
Cloud radio access network (CRAN) offers low-latency and high-speed services to mobile end-users by locating remote radio heads (RRHs) near end-users and centralizing the baseband units (BBUs) corresponding to the RRHs in a central cloud. However, considering the time-varying traffic loads, a self-adjustable base station (BS) can respond to changing traffic loads for meeting user demands is needed. This paper focuses on minimizing the cost of fronthaul establishment and bandwidth consumption in forming a self-adjustable virtual BS (VBS). Since the fronthaul is critical infrastructure of CRAN connecting BBUs and RRHs that affects the VBS formation but cannot be adjusted dynamically, we jointly consider their decision making and formulate it as a two-stage stochastic problem. Since this problem can be linearized to an integer linear program (ILP) but is difficult to solve given a large network scale, we propose an approach called FEBD inspired by Benders decomposition (BD) to achieve the optimal fronthaul connection. Furthermore, we propose a heuristic approach that can quickly adjust the VBS formation in response to user demand. The numerical experiments show that the combined use of FEBD and the heuristic approach provides results that are close to the ILP results with a significantly shorter computation time.
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