论文标题

大规模无细胞的大型MIMO中的能源效率最大化:一种投影梯度方法

Energy Efficiency Maximization in Large-Scale Cell-Free Massive MIMO: A Projected Gradient Approach

论文作者

Mai, Trang C., Ngo, Hien Quoc, Tran, Le-Nam

论文摘要

本文考虑了无细胞的大规模突变输入和多重输出(MIMO)系统中的基本功率分配问题,该系统旨在在每个访问点(AP)和服务质量(QOS)约束下在每个用户的总和限制下最大化总能量效率(EE)。此优化问题的现有解决方案基于求解一系列二阶锥体程序(SECP),其计算复杂性随着网络大小而显着扩展。因此,对于实用的大规模无细胞大规模MIMO系统,它们不可实施。为了解决此问题,我们根据加速投影梯度(APG)方法的框架工作提出了一种迭代功率控制算法。特别是,所提出的方法的每次迭代都是通过简单的封闭形式表达式完成的,其中应用了惩罚方法将约束以惩罚函数的形式带入目标。最后,与基于SOCP的已知解决方案进行了分析证明和数值证明和数值证明的收敛性。仿真结果表明,我们提出的功率控制算法可以达到与现有基于苏金的方法相同的EE,但更重要的是,它的运行时间要低得多(与基于苏金的方法相比,运行时间降低了一到两个数量级)。

This paper considers the fundamental power allocation problem in cell-free massive mutiple-input and multiple-output (MIMO) systems which aims at maximizing the total energy efficiency (EE) under a sum power constraint at each access point (AP) and a quality-of-service (QoS) constraint at each user. Existing solutions for this optimization problem are based on solving a sequence of second-order cone programs (SOCPs), whose computational complexity scales dramatically with the network size. Therefore, they are not implementable for practical large-scale cell-free massive MIMO systems. To tackle this issue, we propose an iterative power control algorithm based on the frame work of an accelerated projected gradient (APG) method. In particular, each iteration of the proposed method is done by simple closed-form expressions, where a penalty method is applied to bring constraints into the objective in the form of penalty functions. Finally, the convergence of the proposed algorithm is analytically proved and numerically compared to the known solution based on SOCP. Simulations results demonstrate that our proposed power control algorithm can achieve the same EE as the existing SOCPs-based method, but more importantly, its run time is much lower (one to two orders of magnitude reduction in run time, compared to the SOCPs-based approaches).

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