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So near, and yet so far: Managing #x2018;far-away#x2019; interferers in dense femto-cell networks

机译:如此接近,但到目前为止:管理‘遥远的’ 干扰密集的毫微微细胞网络

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We expect femto-cells to be massively and densely deployed in the future. Numerous existing works on femto-cell interference management assume that the local topology of interfering femto-cells can be sufficiently approximated through sensing, if not already known in advance. We show that this assumption results in poor throughput performance in dense femto-cell networks. For some cell-edge users, using conventional sensing in dense deployments can result in almost 50 times less instantaneous throughput, as compared to having oracular knowledge of interference topology. This sub-optimality is caused by “far-away” interferers. These are femto-cells that are deployed just far enough such that their presence will not be detected by conventional sensing. We then introduce a mobile sensing scheme to detect these “far-away” interferers by exploiting the inherent mobility of femto-cell users. We show through packet-level simulation that this sensing scheme is able to better approximate the interference topology. This results in significantly improved performance over conventional sensing, in dense deployment scenarios.
机译:我们预计将来毫微微细胞将在未来大规模地部署。关于毫微微小区干扰管理的许多现有作品假设干扰毫微微细胞的局部拓扑可以通过感测,如果尚未提前已知。我们表明,这种假设导致密集的毫微微细胞网络中的吞吐量性能差。对于一些细胞边缘用户,与具有令人讨厌的干扰拓扑知识相比,使用致密部署中的传统感测可能导致瞬时吞吐量的瞬时吞吐量较小。这个次级最优性是由“遥远的&#x201d引起的;干涉者。这些是毫微微细胞,其展开得足够远,使得它们不会通过常规传感来检测它们的存在。然后我们介绍一个移动感测方案来检测这些“遥远的”通过利用毫微微小组用户的固有移动性而干扰。我们通过分组级模拟显示该感测方案能够更好地近似于干扰拓扑。这导致在密集部署方案中对传统感测的性能显着提高。

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