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首页> 外文期刊>Engineering Applications of Artificial Intelligence >A grouping genetic algorithm for the microcell sectorization problem
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A grouping genetic algorithm for the microcell sectorization problem

机译:用于微小区扇区化问题的分组遗传算法

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摘要

The number of wireless users has steadily increased over the last decade, leading to the need for methods that efficiently use the limited bandwidth available. Reducing the size of the cells in a cellular network increases the rate of frequency reuse or channel reuse, thus increasing the network capacity. The drawback of this approach is increased costs associated with installation and coordination of the additional base stations. A code-division multiple-access network where the base stations are connected to the central station by fiber has been proposed to reduce the installation costs. To reduce the coordination costs and the number of handoffs, sectorization (grouping) of the cells is suggested. We propose a dynamic sectorization of the cells, depending on the current sectorization and the time-varying traffic. A grouping genetic algorithm is proposed to find a solution which minimizes costs. The computational results demonstrate the effectiveness of the algorithm across a wide range of problems. The GGA is shown to be a useful tool to efficiently allocate the limited number of channels available.
机译:在过去的十年中,无线用户的数量稳步增长,导致需要有效利用有限的可用带宽的方法。减小蜂窝网络中小区的大小可以提高频率重用或信道重用的速率,从而增加网络容量。这种方法的缺点是与附加基站的安装和协调相关的成本增加。已经提出了一种码分多址网络,其中基站通过光纤连接到中心站,以降低安装成本。为了减少协调成本和切换次数,建议对小区进行分区(分组)。我们建议根据当前的扇区划分和随时间变化的业务量对单元格进行动态分区。提出了一种分组遗传算法,以找到最小化成本的解决方案。计算结果证明了该算法在各种问题上的有效性。 GGA被证明是有效分配有限数量的可用通道的有用工具。

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