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Weighted Sum Energy Efficiency Optimization for Massive MIMO Two-Way Half-Duplex AF Relaying

机译:大规模MIMO两路半双工AF中继的加权总能效优化

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摘要

We consider two-way amplitude and forward half-duplex massive multiple-input multiple output (MIMO) relaying with multiple user-pairs. Most of the existing massive MIMO relaying literature has optimized the network-centric global energy efficiency metric, which is a pseudo-concave (PC) function, and can be optimized using well-known Dinkelbach algorithm. We optimize the user-centric weighted sum energy efficiency (WSEE), which is defined as the weighted sum of energy efficiencies of all the users, and is not a PC function. We propose a successive convex approximation approach to optimize it, and analytically show that this approach yields a Karush-Kuhn-Tucker point of the original WSEE problem. We also reduce the computational complexity of the above approach by approximating it as a second order cone program. We numerically demonstrate the WSEE improvement achieved by the proposed algorithms over baseline equal- and random-power allocation algorithms.
机译:我们考虑双向幅度和具有多个用户对的前向半双工大规模多输入多输出(MIMO)中继。大多数现有的大规模MIMO中继文献都优化了以网络为中心的全局能效度量,该度量是伪凹(PC)功能,可以使用众所周知的Dinkelbach算法进行优化。我们优化了以用户为中心的加权总和能源效率(WSEE),它定义为所有用户的能源效率的加权总和,而不是PC功能。我们提出了一种连续凸逼近方法来对其进行优化,并分析表明该方法产生了原始WSEE问题的Karush-Kuhn-Tucker点。我们还通过将其近似为二阶锥程序来降低了上述方法的计算复杂性。我们用数值方法证明了所提出的算法相对于基线均等功率和随机功率分配算法所实现的WSEE改进。

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