Performances evaluation of different algorithms for PCIs self configuration in LTE

Mariem Krichen, D. Barth, O. Marcé
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引用次数: 9

Abstract

Nowadays, network operators are basically facing two problems: the fast number of subscribers growth and the network congestion. To solve these problems, network operators increase the number of cells, make cells smaller and reserve a subpart of frequencies to Femto cells to offload data traffic. As a consequence, networks manual planning demands a lot of efforts and its cost increases. Self-configuring and self-optimizing mechanisms would be vital to operators to reduce manual planning. This article focuses on the application of these mechanisms in LTE and more specifically on the procedure of Automated configuration of Physical Cell Ids (PCIs). This procedure aims at avoiding conflicts in PCIs allocation. In this article, we first evaluate the performances of 3 relabeling algorithms applied on graphs representing real LTE Macro networks: Random Relabeling algorithm (RR), Smallest available Value algorithm (SV), Distance 3 neighbour label algorithm (D3). Then, we evaluate the performances of the best algorithm applied on graphs representing real LTE networks where Femto cells are connected to Macro cells. Here, we answer the following question: is the selected relabeling algorithm still efficient when we extend its application to Femto cells?.
LTE中pci自配置不同算法的性能评价
目前,网络运营商主要面临两个问题:用户增长过快和网络拥塞。为了解决这些问题,网络运营商增加了小区的数量,使小区更小,并为Femto小区保留了一部分频率,以卸载数据流量。因此,网络人工规划需要大量的工作和成本的增加。自配置和自优化机制对于运营商减少人工规划至关重要。本文重点介绍了这些机制在LTE中的应用,并详细介绍了物理单元id (Physical Cell id, pci)的自动配置过程。这个程序的目的是为了避免在pci分配中的冲突。在本文中,我们首先评估了3种用于表示实际LTE宏网络的图的重标记算法的性能:随机重标记算法(RR),最小可用值算法(SV),距离3邻居标记算法(D3)。然后,我们评估了最佳算法在表示实际LTE网络的图上的性能,其中Femto蜂窝连接到Macro蜂窝。在这里,我们回答了以下问题:当我们将所选择的重新标记算法扩展到Femto细胞时,它是否仍然有效?
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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