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When Green Energy Meets Cloud Radio Access Network: Joint Optimization Towards Brown Energy Minimization

机译:当绿色能源符合云无线电接入网络时:联合优化棕色能量最小化

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摘要

Wireless networks have experienced fast development in the past decades. Various advancing wireless technologies have been proposed. To catch up with the ever-increasing diverse communication needs, cloud-radio access networks (C-RAN), which decouples the baseband processing unit (BBU) from the remote radio head (RRH), has been proposed. On the other hand, it has been widely recognized that huge energy consumption has been raised due to the massive deployment of cellular networks. Lowering the network energy consumption therefore becomes a widely concerned topic. To combat the limitations in traditional power grid, smart grid, with the emphasis on distributed energy resource (DER) and bidirectional energy sharing, is advocated to power the wireless networks. In this paper, we are motivated to investigate a joint RRH-BBU association and energy sharing problem towards brown energy usage minimization in green energy powered C-RAN. The problem is formulated into a mixed integer linear programming (MILP) form. To deal with the computation complexity of solving MILP, a two-phase heuristic polynomial-time algorithm is proposed and evaluated via extensive simulation based studies.
机译:无线网络在过去几十年中经历了快速发展。已经提出了各种推进的无线技术。为了追赶不断增加的多样化通信需求,已经提出了从远程无线电头(RRH)分离的云 - 无线电接入网络(C-RAN),该网络从远程无线电头(RRH)上耦合到基带处理单元(BBU)。另一方面,已经普遍认识到由于蜂窝网络大规模部署,已经提出了巨大的能耗。因此,降低网络能源消耗成为一个广泛有关的主题。为了打击传统电网中的限制,智能电网,强调分布式能源(DER)和双向能量共享,被提倡为无线网络供电。在本文中,我们有动力调查RRH-BBU协会和能量分享问题,朝着绿色能源动力C-RAN中的棕色能量使用最小化。该问题被配制成混合整数线性编程(MILP)形式。为了处理求解MILP的计算复杂性,提出了一种通过基于广泛的模拟的研究评估了一种两相启发式多项式算法。

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