A backhaul-aware cell selection algorithm for heterogeneous cellular networks

A. Domenico, V. Savin, D. Kténas
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引用次数: 40

Abstract

This paper considers heterogeneous cellular networks, where cluster of small cells are deployed to create local hot spots inside the macro cell. In the past, most of the research in this topic has focused on mitigating inter cell interference; however, wireless backhaul has recently emerged as an urgent challenge to enable ubiquitous broadband wireless services at small cells. Hence, we propose a novel cell selection framework, which associates users and heterogeneous access nodes to improve the efficiency in the overall radio and backhaul resource utilization and avoid load congestions. We also model the relationships amongst cell load, resource management, backhaul capacity constraints, and the overall network capacity. Then, we describe the cell selection problem and we present a heuristic algorithm, named as Evolve, to solve it with limited complexity. Our analysis shows that Evolve achieves near optimal performance leading to notable capacity improvements with respect to the classic SINR based association scheme.
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异构蜂窝网络的回程感知蜂窝选择算法
本文考虑异构蜂窝网络,其中部署小蜂窝集群以在宏蜂窝内创建局部热点。在过去,这一主题的大多数研究都集中在减轻细胞间干扰;然而,无线回程最近成为在小型蜂窝中实现无处不在的宽带无线服务的紧迫挑战。因此,我们提出了一种新的小区选择框架,该框架将用户和异构接入节点关联起来,以提高整体无线电和回程资源利用效率,避免负载拥塞。我们还对单元负载、资源管理、回程容量约束和整体网络容量之间的关系进行了建模。然后,我们描述了细胞选择问题,并提出了一种启发式算法,命名为进化,以有限的复杂性来解决它。我们的分析表明,与经典的基于SINR的关联方案相比,Evolve实现了接近最优的性能,从而显著提高了容量。
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