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An efficient DCA based algorithm for power control in large scale wireless networks

机译:基于高尺度无线网络电源控制的高效基于DCA算法

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In recent years, power control and resource allocation techniques for cellular communication systems are very active research areas. Power control is typically used in wireless cellular networks in order to optimize the transmission subject to quality of service (QoS) constraints. One of the most popular power control problems is based on maximizing the weighted sum of data rates under the peak power constraints for all users. It is a difficult nonconvex optimization problem for which standard approach Geometric Programming is not applicable in large scale setting. In this paper, we propose an efficient method based on DC (Difference of Convex functions) programming and DCA (DC Algorithm), an innovative approach in nonconvex programming framework for solving this problem. The purpose is to develop fast and scalable algorithms able to handle large scale systems. The two main challenges in DC programming and DCA that are the effect of DC decomposition and the efficiency of solution methods to convex subproblems are carefully studied. The computational results on several datasets show the robustness as well as the efficiency of the proposed method in terms of both quality and rapidity, and their superiority compared with the standard approach Geometric Programming. (C) 2017 Published by Elsevier Inc.
机译:近年来,蜂窝通信系统的功率控制和资源分配技术是非常活跃的研究领域。功率控制通常用于无线蜂窝网络,以优化经受服务质量(QoS)约束的传输。最流行的功率控制问题之一是基于所有用户的峰值功率约束下最大化的数据速率的加权和。它是一种困难的非渗透优化问题,标准方法几何编程不适用于大规模设置。在本文中,我们提出了一种基于DC(凸函数差异)编程和DCA(DC算法)的有效方法,这是一种用于解决这个问题的非透露编程框架的创新方法。目的是开发快速和可扩展的算法,可以处理大规模系统。仔细研究了DC编程和DCA中的两个主要挑战,仔细研究了DC分解的影响和解决方案方法的效率。几个数据集上的计算结果显示了稳健性以及在质量和快速度方面的提出方法的效率,以及与标准方法几何编程相比的优势。 (c)2017年由elsevier公司发布

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