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User Association With Maximizing Weighted Sum Energy Efficiency for Massive MIMO-Enabled Heterogeneous Cellular Networks

机译:与大规模启用MIMO的异构蜂窝网络的加权总和能效最大化的用户关联

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In this letter, we design an association strategy to maximize the weighted sum energy efficiency (EE) for massive multiple-input and multiple-output (MIMO)-enabled heterogeneous cellular networks. Considering that the final formulated problem is in a sum-of-ratio form, we first need to transform it into a parametric nonfractional form, by which we can achieve its solution through a two-layer iterative algorithm. The outer layer searches the EE parameters and the multipliers associated with signal-interference-plus-noise ratio constraints using Newton-like method, and the inner layer optimizes the association indices using Lagrange multiplier method. Then, we give some convergence and complexity analyses for the proposed algorithm. Numerical results show that the proposed scheme significantly outperforms the existing one on the system throughput and network EE under a certain condition. In addition, we also investigate the impacts of the number of massive antennas and the transmit power of each pico base station on the association performance.
机译:在这封信中,我们设计了一种关联策略,以使大规模启用多输入和多输出(MIMO)的异构蜂窝网络的加权总能效(EE)最大化。考虑到最终提出的问题采用比率总和形式,我们首先需要将其转化为参数非分数形式,通过此形式,我们可以通过两层迭代算法来实现其解决方案。外层使用类牛顿法搜索EE参数和与信号干扰加噪声比约束相关的乘数,内层使用拉格朗日乘数法优化关联索引。然后,我们对该算法进行了一些收敛性和复杂性分析。数值结果表明,在一定条件下,该方案在系统吞吐量和网络EE方面明显优于现有方案。此外,我们还研究了大型天线数量和每个微微基站的发射功率对关联性能的影响。

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