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Joint Sparse Beamforming and Network Coding for Downlink Multi-Hop Cloud Radio Access Networks

机译:下行多跳云无线接入网的联合稀疏波束成形和网络编码

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This paper proposes a joint design of the routing strategy over the fronthaul network and the transmission strategy over the wireless network in a downlink cloud radio access network (C-RAN), in which the remote radio heads (RRHs) are connected to the central processor (CP) via multi-hop routers. The data-sharing strategy is adopted, where the CP multicasts each user's data to all the RRHs serving this user via the multihop fronthaul network, which then cooperatively serve the users through joint beamforming. Such a setting naturally provides an opportunity for applying the technique of network coding to efficiently reduce the multicast traffic in the fronthaul network. A novel cross-layer optimization framework is then investigated, where the RRH's beamforming vectors as well as the user- RRH association in the physical-layer, and the network coding design in the network-layer are jointly optimized to maximize the throughput of C- RAN subject to fronthaul link capacity constraints. This paper proposes a two-stage algorithm to solve this problem using the techniques of sparse optimization and successive convex approximation. Simulation results are provided to verify the effectiveness of the proposed cross-layer design in the downlink multi- hop C-RAN.
机译:本文提出了在下行云无线接入网(C-RAN)中将前传网络上的路由策略与无线网络上的传输策略进行联合设计的方案,其中将远程无线头(RRH)连接到中央处理器(CP)通过多跳路由器。采用数据共享策略,CP通过多跳前传网络将每个用户的数据多播到为该用户服务的所有RRH,然后再通过联合波束成形为用户提供服务。这样的设置自然为应用网络编码技术提供了机会,以有效减少前传网络中的多播流量。然后研究了一种新颖的跨层优化框架,其中对RRH的波束形成向量以及物理层中的用户RRH关联以及网络层中的网络编码设计进行了联合优化,以最大程度地提高C- RAN受前传链路容量限制。本文提出了一种两阶段算法,利用稀疏优化和连续凸逼近技术来解决该问题。提供仿真结果以验证所提出的跨层设计在下行链路多跳C-RAN中的有效性。

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