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arXiv 1602.08273cs.ITmath.IT
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基于干扰对齐的多小区网络全局最优基站分簇

Globally Optimal Base Station Clustering in Interference Alignment-Based Multicell Networks

Rasmus Brandt, Rami Mochaourab, Mats Bengtsson

摘要:

基于干扰对齐的协调预编码是未来无线多小区网络中提高吞吐量的一种很有前途的技术。在小型网络中,所有基站通常可以联合协调它们的预编码。然而,在大型网络中,由于信道状态信息(CSI)获取开销非常高,因此需要进行基站集群。在这项工作中,我们提供了一个分支定界算法找到全局最优的基站集群。该算法主要用于对现有的次优聚类方案进行基准测试。我们提出了一个通用的用户吞吐量模型,它只依赖于长期的CSI统计。该模型假设集群内干扰对齐,并能够考虑CSI采集开销。通过最佳优先搜索枚举搜索树,并修剪可证明不存在最优解的子树,该方法收敛到最优解。修剪是使用专门推导的界限,这利用了吞吐量模型中的一些假设结构。经验表明,所提出的方法具有平均复杂度是数量级低于穷举搜索。

英文摘要:

Coordinated precoding based on interference alignment is a promising technique for improving the throughputs in future wireless multicell networks. In small networks, all base stations can typically jointly coordinate their precoding. In large networks however, base station clustering is necessary due to the otherwise overwhelmingly high channel state information (CSI) acquisition overhead. In this work, we provide a branch and bound algorithm for finding the globally optimal base station clustering. The algorithm is mainly intended for benchmarking existing suboptimal clustering schemes. We propose a general model for the user throughputs, which only depends on the long-term CSI statistics. The model assumes intracluster interference alignment and is able to account for the CSI acquisition overhead. By enumerating a search tree using a best-first search and pruning sub-trees in which the optimal solution provably cannot be, the proposed method converges to the optimal solution. The pruning is done using specifically derived bounds, which exploit some assumed structure in the throughput model. It is empirically shown that the proposed method has an average complexity which is orders of magnitude lower than that of exhaustive search.

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