From Immune Cells to Self-Organizing Ultra-Dense Small Cell Networks
From Immune Cells to Self-Organizing Ultra-Dense Small Cell Networks
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DOI：
10.1109/jsac.2016.2544638
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发表时间：
2016-04-01
影响因子：
16.4
通讯作者：
Fettweis, Gerhard P.
中科院分区：
文献类型：
--
作者：
Klessig, Henrik;Oehmann, David;Fettweis, Gerhard P.
为了应对未来十年内无线流量需求的爆炸式增长，运营商正在以更密集的方式在其宏蜂窝网络中部署低功率基站。这类网络通常被称为异构或超密集小蜂窝网络，其部署在回程、容量提供以及时空波动的流量负载动态方面带来了诸多挑战。自组织网络（SON）解决方案已被定义用于克服这些挑战。由于自组织现象存在于众多生物系统中，我们确定了免疫系统自我调节的设计原则，并就超密集小蜂窝网络进行了类比。特别是，我们开发了一种人工免疫系统（AIS）的数学模型，该模型可根据本地流量需求自主激活或停用小蜂窝。所提出的基于AIS的SON方法的主要目标是提高能源效率和改善小区边缘吞吐量。作为原理验证，进行了系统级模拟，对生物启发算法在各种参数设置下进行了评估，例如小蜂窝激活速度和停用延迟。通过地理位置展示不确定性的时空变化流量分析证明了所提出的基于AIS的SON方法的稳健性。
In order to cope with the wireless traffic demand explosion within the next decade, operators are underlying their macrocellular networks with low power base stations in a more dense manner. Such networks are typically referred to as heterogeneous or ultra-dense small cell networks, and their deployment entails a number of challenges in terms of backhauling, capacity provision, and dynamics in spatio-temporally fluctuating traffic load. Self-organizing network (SON) solutions have been defined to overcome these challenges. Since self-organization occurs in a plethora of biological systems, we identify the design principles of immune system self-regulation and draw analogies with respect to ultra-dense small cell networks. In particular, we develop a mathematical model of an artificial immune system (AIS) that autonomously activates or deactivates small cells in response to the local traffic demand. The main goal of the proposed AIS-based SON approach is the enhancement of energy efficiency and improvement of cell-edge throughput. As a proof of principle, system level simulations are carried out in which the bio-inspired algorithm is evaluated for various parameter settings, such as the speed of small cell activation and the delay of deactivation. Analysis using spatio-temporally varying traffic exhibiting uncertainty through geo-location demonstrates the robustness of the AIS-based SON approach proposed.