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Base Station clustering in heterogeneous network with finite backhaul capacity

机译：具有有限回程容量的异构网络中的基站集群

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This paper considers the Base Station (BS) clustering in a downlink heterogeneous network with finite backhaul capacity. We consider a tree structure network where each BS has only one incoming link and several outgoing links. The objective is to maximize the minimum rate among all users while satisfying the backhaul capacity constraint and the per-BS power constraint. We propose an algorithm that combines the bisection and the Alternating Direction Method of Multipliers (ADMM). The bisection search is conducted for the minimum rate. When it is given, we use ADMM to check the feasibility of the network while obeying the backhaul and power constraints. There are two steps involved in ADMM: i) a second order conic programming is used to calculate the beamformer; ii) a closed-form rule is used to determine the BS clustering. Due to the non-convexity and the non-smoothness, ADMM is not guaranteed to solve the problem. Therefore, we propose a revise step to further improve the performance. The simulation results show that the proposed algorithm outperforms the heuristic method and the revise step does improve the performance in all considered scenarios.
机译：本文考虑具有有限回程容量的下行链路异构网络中的基站（BS）集群。我们考虑一个树形结构的网络，其中每个BS只有一个输入链路和几个输出链路。目的是在满足回程容量约束和每基站功率约束的同时，使所有用户之间的最小速率最大化。我们提出了一种将二等分和乘法器交替方向方法（ADMM）相结合的算法。进行二等分搜索以获取最小速率。当给出时，我们使用ADMM来检查网络的可行性，同时遵守回程和功率限制。 ADMM涉及两个步骤：i）使用二阶圆锥编程来计算波束形成器; ii）使用封闭式规则来确定BS聚类。由于不凸性和不光滑性，因此不能保证ADMM解决该问题。因此，我们提出了一个修订步骤，以进一步提高性能。仿真结果表明，所提出的算法优于启发式算法，并且在所有考虑的情况下，修正步骤的确提高了性能。

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