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首页> 外文期刊>IEEE Journal on Selected Areas in Communications >Deploying Dense Networks for Maximal Energy Efficiency: Small Cells Meet Massive MIMO
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Deploying Dense Networks for Maximal Energy Efficiency: Small Cells Meet Massive MIMO

机译:部署密集网络以实现最大的能源效率:小型蜂窝满足大规模MIMO

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What would a cellular network designed for maximal energy efficiency look like? To answer this fundamental question, tools from stochastic geometry are used in this paper to model future cellular networks and obtain a new lower bound on the average uplink spectral efficiency. This enables us to formulate a tractable uplink energy efficiency (EE) maximization problem and solve it analytically with respect to the density of base stations (BSs), the transmit power levels, the number of BS antennas and users per cell, and the pilot reuse factor. The closed-form expressions obtained from this general EE maximization framework provide valuable insights on the interplay between the optimization variables, hardware characteristics, and propagation environment. Small cells are proved to give high EE, but the EE improvement saturates quickly with the BS density. Interestingly, the maximal EE is achieved by also equipping the BSs with multiple antennas and operate in a “massive MIMO” fashion, where the array gain from coherent detection mitigates interference and the multiplexing of many users reduces the energy cost per user.
机译:为实现最大能效而设计的蜂窝网络会是什么样?为了回答这个基本问题,本文使用随机几何工具对未来的蜂窝网络进行建模,并获得平均上行链路频谱效率的新下限。这使我们能够制定一个可解决的上行链路能量效率(EE)最大化问题,并针对基站(BS)的密度,发射功率电平,每个小区的BS天线和用户数以及导频重用进行分析解决因子。从此通用EE最大化框架获得的闭式表达式可提供有关优化变量,硬件特性和传播环境之间相互作用的有价值的见解。事实证明,小蜂窝小区具有较高的EE,但是随着BS密度的提高,EE的提高很快就会饱和。有趣的是,通过为BS配备多个天线并以“大规模MIMO”方式工作,可以实现最大的EE,其中相干检测的阵列增益可减轻干扰,许多用户的多路复用降低了每个用户的能源成本。

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