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Mobile Networks and Applications

, Volume 23, Issue 2, pp 308–317 | Cite as

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

  • Xiangping Zhai
  • Xiaoxiao Guan
  • Jiabin Yuan
  • Hu Liu
  • Joel J. P. C. Rodrigues
Article
  • 179 Downloads

Abstract

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.

Keywords

D2D communications Energy efficiency Resource allocation Fractional programming Duality 

Notes

Acknowledgements

The work in this paper was partially supported by the Special Foundation for State Major Basic Research Program of China under Grant No. 2017YFB0802303, in part by the National Natural Science Foundation of China under Grant No. 61701231, in part by FCT - Fundação para a Cie~ncia e a Tecnologia funding Project UID/EEA/500008/2013, in part by the Government of Russian Federation under Grant 074-U01, and in part by Finep, with resources from Funttel under Grant 01.14.0231.00, under the Centro de Referencia em Radiocomunicações-CRR project of the Instituto Nacional de Telecomunicações (Inatel), Brazil. The material in this paper was presented in part at the 3rd IEEE International Conference on Cloud Computing and Security, Nanjing, P. R. China, 2017.

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjingChina
  2. 2.Collaborative Innovation Center of Novel Software Technology and IndustrializationNanjingChina
  3. 3.National Institute of Telecommunications (Inatel)Santa Rita do SapucaíBrazil
  4. 4.Instituto de TelecomunicaçõesLisboaPortugal
  5. 5.ITMO UniversitySaint PetersburgRussia
  6. 6.University of Fortaleza (UNIFOR)FortalezaBrazil

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