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Aggregation of variables in load models for interference-coupled cellular data networks

机译:干扰耦合蜂窝数据网络负载模型中的变量汇总

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In order to meet increasing traffic demands, future generations of cellular networks are characterized by decreasing cell sizes at full frequency reuse. Due to inevitable inter-cell interference, load conditions in neighboring cells can no longer be considered independent. Unfortunately, the adequate flow level model for such a setup is analytically intractable. Utilizing aggregation techniques, which were originally proposed to analyze large state models in economics, we propose a framework to compute the average base station loads based on an approximation of the joint stationary distribution of the number of active flows in all cells. The technique proposed requires solving a system of linear equations whose dimension increases exponentially with the number of cells. Since such a system is essentially intractable for large networks, we propose a fixed point algorithm to compute approximate base station loads based on the notion of average interference. Numerical results validate the accuracy of both modeling techniques. The modeling approach presented in this paper is essential for accurate characterization of cell throughput as well as base station energy consumption under varying load conditions.
机译:为了满足日益增长的业务需求,蜂窝网络的未来世代的特征在于在全频率复用下减小小区大小。由于不可避免的小区间干扰,相邻小区中的负载条件不再被认为是独立的。不幸的是,在这种情况下,足够的流量水平模型很难分析。利用最初提出的用于分析经济学中大状态模型的聚合技术,我们提出了一个框架来计算平均基站负载,该框架基于所有小区中活动流数量的联合平稳分布的近似值。提出的技术需要求解线性方程组,其线性度随单元格数量呈指数增加。由于这样的系统对于大型网络基本上是难以处理的,因此我们提出了一种定点算法,用于基于平均干扰的概念来计算近似的基站负载。数值结果验证了两种建模技术的准确性。本文提出的建模方法对于准确表征小区吞吐量以及在变化的负载条件下的基站能耗至关重要。

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