Treating Interference as Noise in Cellular Networks: A Stochastic Geometry Approach
Treating Interference as Noise in Cellular Networks: A Stochastic Geometry Approach
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DOI：
10.1109/twc.2019.2959773
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发表时间：
2020-03-01
影响因子：
10.4
通讯作者：
Clerckx, Bruno
中科院分区：
文献类型：
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作者：
Bacha, Mudasar;Di Renzo, Marco;Clerckx, Bruno
当干扰足够弱时，将干扰视为噪声（TIN）的干扰管理技术是最佳的。最近已经提出了基于TIN最优性条件的调度算法，例如，以应用于设备到设备通信。然而，TIN从未被应用于蜂窝网络。在这项工作中，我们提出了一个调度算法应用到蜂窝网络，是基于TIN的最优性条件。在所提出的调度算法中，每个基站（BS）首先在其覆盖区域内随机选择一个用户设备（UE），然后检查TIN最优性条件。如果不满足后一条件，则BS被关闭。为了评估三角网应用于蜂窝网络的性能，我们介绍了一个分析框架的援助随机几何理论。我们开发，特别是，易于处理的信号干扰噪声比（SINR）的覆盖概率和蜂窝网络的平均速率的表达式。此外，我们进行渐近分析，找到最佳的系统参数，最大化的SINR覆盖概率。通过使用优化的系统参数，它示出了TIN应用于蜂窝网络产生显着的增益的SINR覆盖概率和平均速率。具体来说，数值结果表明，平均速率增益的顺序为21%，比传统的调度算法。
The interference management technique that treats interference as noise (TIN) is optimal when the interference is sufficiently weak. Scheduling algorithms based on the TIN optimality condition have recently been proposed, e.g., for application to device-to-device communications. TIN, however, has never been applied to cellular networks. In this work, we propose a scheduling algorithm for application to cellular networks that is based on the TIN optimality condition. In the proposed scheduling algorithm, each base station (BS) first randomly selects a user equipment (UE) in its coverage region, and then checks the TIN optimality conditions. If the latter conditions are not fulfilled, the BS is turned off. In order to assess the performance of TIN applied to cellular networks, we introduce an analytical framework with the aid of stochastic geometry theory. We develop, in particular, tractable expressions of the signal-to-interference-and-noise ratio (SINR) coverage probability and average rate of cellular networks. In addition, we carry out asymptotic analysis to find the optimal system parameters that maximize the SINR coverage probability. By using the optimized system parameters, it is shown that TIN applied to cellular networks yields significant gains in terms of SINR coverage probability and average rate. Specifically, the numerical results show that average rate gains of the order of 21% over conventional scheduling algorithms are obtained.