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On Semi-Static Interference Coordination under Proportional Fair Scheduling in LTE Systems

机译:LTE系统比例公平调度下的半静态干扰协调

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In this paper we consider the design of semi-static inter-cell interference coordination schemes for LTE networks. In this approach, base stations coordinate the power settings per resource block over long time spans such as seconds. In order to optimize the power settings, one needs to employ models which predict the rate of terminals over the next coordination period under the usage of a given power setting. However, these models are typically quite simple and neglect the impact from fading as well as from dynamic resource allocation performed at the base stations on a millisecond basis. Ignoring such properties of OFDMA networks leads therefore to suboptimal transmit power settings. In this paper, we study the impact from a precise rate prediction model that accurately accounts for fading and dynamic resource allocation. On the down-side, this more precise model leads to a much more involved optimization problem to be solved once per coordination period. We propose two different heuristic methods to deal with this problem. Especially the usage of genetic algorithm results to be promising to counteract the complexity increase. We then study the overall system performance and find precise rate prediction models to be essential for semi-static interference coordination as they provide significant performance improvements in comparison to approaches with simpler models.
机译:在本文中,我们考虑了LTE网络的半静态间干扰协调方案的设计。在这种方法中,基站在长时间跨越诸如秒的长时间跨度坐标每个资源块的电源设置。为了优化电力设置,需要采用在给定电源设置的使用下预测下一个协调周期的终端速率的模型。然而,这些模型通常非常简单,忽略衰落以及从基站上执行的动态资源分配以毫秒为基础。因此,忽略OFDMA网络的这种属性导致次优发电电源设置。在本文中,我们研究了精确率预测模型的影响,可以准确地考虑衰落和动态资源分配。在下一侧,这种更精确的模型导致每次协调期间才能解决一次更多的优化问题。我们提出了两种不同的启发式方法来处理这个问题。特别是遗传算法的使用导致抵消复杂性的增加。然后,我们研究了整体系统性能,并找到了精确的速率预测模型,对于半静态干扰协调至关重要,因为它们提供了具有更简单模型的方法的显着性能改进。

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