System Cost Minimization in Cloud RAN With Limited Fronthaul Capacity
System Cost Minimization in Cloud RAN With Limited Fronthaul Capacity
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DOI：
10.1109/twc.2017.2682079
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发表时间：
2017-05
影响因子：
10.4
通讯作者：
Jianhua Tang;Wee Peng Tay;Tony Q. S. Quek;B. Liang
中科院分区：
文献类型：
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作者：
Jianhua Tang;Wee Peng Tay;Tony Q. S. Quek;B. Liang
云无线接入网（C-RAN）是一种将RAN和云计算融合在一起的新一代无线接入网。在本文中，我们将C-RAN的基带单元（BBU）池视为虚拟机（VM）的集合。我们允许每个用户设备（UE）与BBU池中的多个VM相关联，并且每个远程无线电头端（RRH）只能服务有限数量的UE。在此模型下，我们联合优化的BBU池中的VM激活和稀疏波束成形的协调RRH集群，这是有限的前传容量的约束，以最大限度地减少C-RAN的系统成本。我们将此问题表示为混合整数非线性规划问题，然后提出有效的方法来优化活动VM的数量以及稀疏波束成形向量。此外，我们推导出一个封闭形式的解决方案的波束形成向量。仿真结果表明，我们提出的算法有更好的性能比基准算法的系统成本和鲁棒性。
Cloud radio access network (C-RAN) is emerging as a potential alternative for the next generation RAN by merging RAN and cloud computing together. In this paper, we consider the baseband unit (BBU) pool of C-RAN as a collection of virtual machines (VMs). We allow each user equipment (UE) to associate with multiple VMs in the BBU pool, and each remote radio head (RRH) can only serve a limited number of UEs. Under this model, we jointly optimize the VM activation in the BBU pool and sparse beamforming in the coordinated RRH cluster, which is constrained by limited fronthaul capacity, to minimize the system cost of C-RAN. We formulate this problem as a mixed-integer nonlinear programming problem, and then propose efficient methods to optimize the number of active VMs, as well as the sparse beamforming vectors. Moreover, we derive a closed-form solution for the beamforming vectors. Simulation results suggest that our proposed algorithms have better performance than the benchmark algorithms in terms of both system cost and robustness.