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Minimum Rate Maximization for Wireless Powered Cloud Radio Access Networks

机译:无线供电的云无线电接入网的最小速率最大化

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This paper studies the optimization of signal processing strategies for downlink and uplink of a cloud radio access network (C-RAN) that serves wireless powered users with non-linear energy harvesting (EH) circuits. On the downlink, a baseband processing unit (BBU) sends radio frequency signals to the users through a set of remote radio heads (RRHs), which is centrally managed by the BBU via finite-fronthaul links. Then, each user splits the received signal for information decoding and EH by utilizing the power splitting circuit. By using the harvested energy, each user communicates with the BBU via the RRHs on the uplink. In this paper, we tackle a problem of maximizing the minimum uplink rate of the users subject to the minimum downlink rate constraint as well as the per-node transmit power and fronthaul capacity constraints. To overcome the non-convexity of the problem, we propose an iterative algorithm based on a successive convex approximation method, which obtains a locally optimal solution. Numerical results confirm the effectiveness of the proposed techniques for C-RAN systems with battery-limited users.
机译:本文研究了为无线供电用户提供非线性能量收集(EH)电路的云无线电接入网(C-RAN)的下行链路和上行链路的信号处理策略的优化。在下行链路上,基带处理单元(BBU)通过一组远程无线电头(RRH)将射频信号发送给用户,这些无线电头由BBU通过有限前途链路进行集中管理。然后,每个用户利用功率分配电路将接收到的信号分配给信息解码和EH。通过使用收集的能量,每个用户都通过上行链路上的RRH与BBU通信。在本文中,我们解决了在最小下行链路速率约束以及每个节点的发射功率和前传容量约束的情况下最大化用户的最小上行链路速率的问题。为了解决该问题的非凸性,我们提出了一种基于逐次凸逼近法的迭代算法,该算法获得了局部最优解。数值结果证实了所提出的技术对于电池受限用户的C-RAN系统的有效性。

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