Proportional Fair Energy-Efficient Resource Allocation in Energy-Harvesting-Based Wireless Networks

Byung Chang Chung, Kisong Lee, Dong Ho Cho

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

In energy-limited networks, battery-powered nodes suffer from energy famine, which can reduce network lifetime and affect the robustness of networks. To alleviate an energy problem, it is possible to harvest energy from ambient radio frequency signals. In this paper, we consider a proportional fair energy efficiency, which jointly considers energy efficiency and fairness in energy-harvesting-based wireless networks. We formulate a nonconvex optimization problem for solving subchannel and power allocation in order to maximize proportional fair energy efficiency. Using nonlinear fractional programming, we transform the optimization problem into a tractable convex problem. We also derive the solution of the transformed problem and propose a resource allocation algorithm using an iterative method. In addition, we prove the convergence of the proposed algorithm in view of a suboptimal point. Through intensive simulations, we compare the performance of our proposed algorithm with those of conventional algorithms. It is shown that the proposed algorithm improves fairness considerably while maintaining energy efficiency, compared with conventional algorithms.

Original languageEnglish
Article number7572874
Pages (from-to)2106-2116
Number of pages11
JournalIEEE Systems Journal
Volume12
Issue number3
DOIs
StatePublished - Sep 2018

Keywords

  • energy efficiency
  • Energy harvesting (EH)
  • optimization
  • proportional fairness
  • resource allocation
  • simultaneous wireless information and power transfer

Fingerprint

Dive into the research topics of 'Proportional Fair Energy-Efficient Resource Allocation in Energy-Harvesting-Based Wireless Networks'. Together they form a unique fingerprint.

Cite this