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New Method of Energy Efficient Subcarrier Allocation Based on Evolutionary Game Theory

  • De-gan Zhang
  • Chen Chen
  • Yu-ya Cui
  • Ting Zhang
Article
  • 59 Downloads

Abstract

Since there is a competition between subcarriers because FBMC (Filter Bank Multicarrier) modulation technology does not need subcarriers to be orthogonal to each other, we consider the evolutionary game method to optimize subcarrier allocation. Because the adjacent subcarriers do not need to be orthogonal to each other in FBMC, there is conflict and competition, thus the evolutionary game theory is used to optimize the subcarrier allocation problem. We innovatively introduced the channel state matrix to show the quality of subcarriers. Considering the height of secondary user and base station’s antenna, the total data transmission rate limit, total power consumption constraint and power consumption constraint on a single subcarrier, a nonlinear fractional programming problem is established where maximum energy efficiency is the objective function, total data transmission rate limit, total power consumption constraint and power consumption constraint on a single subcarrier are constraint conditions. The utility function for each secondary user is established when the evolutionary game operator is designed. When the utility function becomes optimal, the evolutionary game reaches Nash equilibrium, and the strategy combination is considered to be the energy efficient resource allocation scheme. Through experimental simulation, EESA-EG proposed in this paper gives the most reasonable subcarrier allocation scheme, allocates more subcarriers for the subcarriers with better channel state and the energy efficiency in EESA-EG is optimal.

Keywords

Cognitive radio network FBMC Resource allocation Evolution game Energy efficient optimization 

Notes

Acknowledgments

This research work is supported by National Natural Science Foundation of China (Grant No. 61571328), Tianjin Key Natural Science Foundation (No.13JCZDJC34600), CSC Foundation (No. 201308120010), Major projects of science and technology in Tianjin (No.15ZXDSGX 00050), Training plan of Tianjin University Innovation Team (No.TD12-5016, No.TD13-5025), Major projects of science and technology for their services in Tianjin (No.16ZXFWGX00010, No.17YFZC GX00360), the Key Subject Foundation of Tianjin(15JCYBJC 46500), Training plan of Tianjin 131 Innovation Talent Team (No.TD2015-23).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • De-gan Zhang
    • 1
    • 2
    • 3
  • Chen Chen
    • 1
    • 2
  • Yu-ya Cui
    • 1
    • 2
  • Ting Zhang
    • 1
    • 2
  1. 1.Key Laboratory of Computer Vision and System (Tianjin University of Technology), Ministry of EducationBeijingChina
  2. 2.Tianjin Key Lab of Intelligent Computing & Novel software TechnologyTianjin University of TechnologyXiqingChina
  3. 3.School of Electronic and Information EngineeringUniversity of SydneySydneyAustralia

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