基于改进Mothflame优化的异构网络干扰管理

Fajar Setiawan, I. Wayan Mustika, Khampaserth Xaphakdy, D. D. Ariananda
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引用次数: 1

摘要

为了减少干扰,提高网络性能,需要对网络进行资源块管理。在异构网络中,飞基站部署在宏基站内,协同层和跨层干扰仍然是该研究领域的一个问题。这种干扰会导致系统性能的下降。然后需要适当的资源块管理来减少干扰。利用离散细菌觅食优化(DBFO)和随机优化(random scheme)等多种优化方法进行了减少干扰的研究。然而,利用改进的离散母焰优化算法(DMFO)方法进行干扰抑制的研究从未有过。因此,本文提出了一种基于自然启发的DMFO算法来解决资源块分配问题。结合DMFO算法的异构系统模型显示出明显的加速效果。信噪比(SINR)图的累积分布函数(CDF)证明了DMFO方案比DBFO方案和随机方案具有更好的性能。
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Interference Management in Heterogeneous Networks using Modified Mothflame Optimization
Resource block management for network optimization is necessary in order to minimize interference, thus improving network performance. In a heterogeneous network where the femtocells are deployed inside a macrocell, the co-tier and cross-tier interference are still an issue in this research area. This interference can lead to degradation of the system performance. A proper resource block management is then required to reduce the interference. Several studies to reduce the interference have been conducted using various optimization methods, such as discrete bacterial foraging optimization (DBFO) and random scheme. However, interference reduction using a modified discrete mothflame optimization algorithm (DMFO) method has never been carried out before. Thus, a DMFO algorithm, which is one of nature-inspired algorithms, has been proposed to solve the resource block allocation problem. A heterogeneous system model combined with the DMFO algorithm has shown some significant acceleration. Compared to the DBFO and random scheme, DMFO was found to yield a better performance as proven by cumulative distribution function (CDF) of signal to interference noise ratio (SINR) graphic.
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