Optimal Power Allocation Scheme for Energy Efficiency Maximization in Distributed Antenna Systems

Optimal Power Allocation Scheme for Energy Efficiency Maximization in Distributed Antenna Systems
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DOI:
10.1109/tcomm.2014.2385772
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发表时间:
2015-02
影响因子:
8.3
通讯作者:
Heejin Kim;Sang-Rim Lee;Changick Song;Kyoung-Jae Lee;Inkyu Lee
Heejin Kim;Sang-Rim Lee;Changick Song;Kyoung-Jae Lee;Inkyu Lee
中科院分区:
计算机科学2区
文献类型:
--
作者:
Heejin Kim;Sang-Rim Lee;Changick Song;Kyoung-Jae Lee;Inkyu Lee

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在本文中,我们提出了一种分布式天线系统(DAS)的功率分配方法,以最大限度地提高能量效率(EE),这是定义为传输速率的总消耗功率的比率。不同于传统的EE最大化计划,需要迭代的数值方法,我们得到的最优解作为一个封闭的形式,通过解决Karush-Kuhn-Tucker条件。所得到的封闭形式的表达是适用于DAS与任意数量的分布式天线(DA)端口和一般每DA端口功率约束,也保证是全局最优的。然后,我们提供了几个有趣的观察建议EE最大化的功率分配方案。基于这些结果,我们提出了一个简化的实用功率分配方法,采用DA端口选择和计算的功率水平在一个分布式的方式。通过蒙特卡罗模拟,我们表明,所提出的最优功率分配方法产生的EE相同的穷举搜索,显着降低计算复杂度。此外,它表明,所提出的简化的功率分配方法的基础上DA端口的选择表现出较小的性能损失相比,最优算法的系统开销显着减少。
In this paper, we present a power allocation method for a distributed antenna system (DAS) to maximize energy efficiency (EE), which is defined as the ratio of the transmission rate to the total consumed power. Different from conventional EE maximization schemes that require iterative numerical methods, we derive the optimal solution as a closed form by solving Karush-Kuhn-Tucker conditions. The obtained closed-form expression is applicable to DAS with an arbitrary number of distributed antenna (DA) ports and general per-DA port power constraints and is also guaranteed to be globally optimum. Then, we provide several interesting observations on the proposed EE maximizing power allocation scheme. Based on these results, we propose a simplified practical power allocation method that employs the DA port selection and computes the power level in a distributed manner. Through Monte Carlo simulations, we show that the proposed optimal power allocation method produces the EE identical to exhaustive search with significantly reduced computational complexity. In addition, it is shown that the proposed simplified power allocation method based on the DA port selection exhibits little performance loss compared to the optimal algorithm with a remarkable reduction in the system overhead.