5G异构网络随机几何干扰模型

Cuili Wang, Chao Yang, Lin Liu, Ping Wang, Heng Liu
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引用次数: 2

摘要

为了满足日益增长的数据速率需求,下一代移动通信(5G)正朝着异构、不规则和复杂的方向发展。这将导致更复杂的干扰环境。因此,传统的固定几何六边形模型已不再适用。为了更准确地评估5G异构网络的性能,本文提出了一种基于随机几何的下行两层异构蜂窝网络(HCN),该网络考虑了BSs之间的层间和层内空间相关性。我们对边缘和热点区域的平均信噪比和平均吞吐量进行了实证研究。与传统的固定几何六边形模型相比,随机几何模型更适合实际的5G异构蜂窝网络。
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Stochastic Geometry Interference Model for 5G Heterogeneous Network
In order to meet the increasing demand of data rate, the next generation Mobile Communications (5G) are becoming more heterogeneous, irregular and complex. This will lead to more complex interference environment. So the traditional fixed geometry hexagon model is no longer applicable. In order to more accurately evaluate the performance of the 5G heterogeneous network, in this paper, we proposes to analyze a downlink two-tiers heterogeneous cellular network (HCN) based on the stochastic geometry, which considers the inter-layer and intra-layer spatial correlation between the BSs. We present our empirical study on average SINR and average throughput for edge and hotspot areas. By comparing with the traditional fixed geometry hexagon model, the stochastic geometry model is more suitable and accurate for the actual 5G heterogeneous cellular networks.
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