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Low Complexity Node Clustering in Cloud-RAN for Service Provisioning and Resource Allocation

机译:Cloud-RAN中用于服务供应和资源分配的低复杂性节点群集

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Auction-based service provisioning and resource allocation have demonstrated strong potential in Cloud-RAN wireless network architecture and heterogeneous networks for effective resource sharing. One major technical challenge is the integration of interference constraints in auction-based solutions. In this work we transform the interference constraint requirement into a set of linear constraints on each cluster. We tackle the generally NP-hard clustering problem by developing a novel practical suboptimal solution that can meet our design requirement. Our novel algorithm utilizes the properties of chordal graphs and applies Lexicographic Breadth First Search (Lex-BFS) algorithm for cluster splitting. This polynomial time approximate algorithm searches for maximal cliques in a graph by generating strong performance in terms of subgraph density and probability of optimal clustering without suffering from the high complexity of the optimal solution.
机译:基于拍卖的服务供应和资源分配在Cloud-RAN无线网络架构和异构网络中显示出强大的潜力,可实现有效的资源共享。一项主要技术挑战是将干扰约束条件整合到基于拍卖的解决方案中。在这项工作中,我们将干扰约束要求转换为每个群集上的一组线性约束。我们通过开发可以满足我们设计要求的新型实用次优解决方案来解决一般的NP硬聚类问题。我们的新颖算法利用了弦图的性质,并应用词法广度优先搜索(Lex-BFS)算法进行聚类分割。该多项式时间近似算法通过在子图密度和最优聚类概率方面产生强大的性能,而不会受到最优解的高复杂度的影响,从而在图中搜索最大团。

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