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Energy-Efficiency Maximization with Non-linear Fractional Programming for Intelligent Device-to-Device Communications

机译:非线性分数规划的智能设备间通信节能最大化

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摘要

With the exponential growth of wireless users and their traffic demands, it is greatly increasing for the demand of the scarce spectrum resources in the communication networks. In order to enhance the performance of the wireless networks such as end-to-end delay, energy efficiency and throughput, the device-to-device (D2D) communication has been attracted more attention because the two devices in close proximity can communicate directly without traversing the central base station. However, most of users are very sensitive to the battery. Therefore, we aim to maximize the energy efficiency of wireless communication system in the context of underlaying device-to-device communication in this paper, We focus on the formulated power control and resource allocation problem which is non-convex in the fractional form. We reduce it from the power allocation of all users to the joint power and subchannel allocation of D2D users. Then, we tackle it by an iterative approximation algorithm leveraging to the properties of fractional programming. There are two studied cases for the subchannel allocation. One can be solved by the penalty function approach, and the other can be solved by the dual decomposition as well as sub-gradient method. Accordingly, we propose a dual-based algorithm in general. Numerical simulations demonstrate that the proposed algorithms outperform the conventional algorithm in terms of the energy efficiency.
机译:随着无线用户及其流量需求的指数增长,对通信网络中稀缺频谱资源的需求正在大大增加。为了增强无线网络的性能(例如端到端延迟,能效和吞吐量),设备到设备(D2D)通信已引起了更多关注,因为两个紧邻的设备可以直接通信而无需遍历中央基站。但是,大多数用户对电池非常敏感。因此,本文旨在在底层设备到设备通信的背景下最大化无线通信系统的能效。我们着重于公式化的功率控制和资源分配问题,该问题是分数形式的非凸性。我们将其从所有用户的功率分配减少到D2D用户的联合功率和子信道分配。然后,我们利用小数编程的性质,通过迭代逼近算法解决该问题。对于子信道分配,有两种研究情况。一个可以通过罚函数法来解决,另一个可以通过对偶分解以及子梯度法来解决。因此,我们总体上提出了一种基于对偶的算法。数值仿真表明,所提出的算法在能效方面优于传统算法。

著录项

  • 来源
    《Mobile networks & applications》 |2018年第2期|308-317|共10页
  • 作者单位

    College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics,Collaborative Innovation Center of Novel Software Technology and Industrialization;

    College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics,Collaborative Innovation Center of Novel Software Technology and Industrialization;

    College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics,Collaborative Innovation Center of Novel Software Technology and Industrialization;

    College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics,Collaborative Innovation Center of Novel Software Technology and Industrialization;

    National Institute of Telecommunications (Inatel),Instituto de Telecomunicações,ITMO University,University of Fortaleza (UNIFOR);

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    D2D communications; Energy efficiency; Resource allocation; Fractional programming; Duality;

    机译:D2D通信;能效;资源分配;分形编程;对偶性;

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