Skip to main navigation Skip to search Skip to main content

Energy-efficient power allocation with individual and sum power constraints

  • Peter He*
  • , Shan Zhang
  • , Lian Zhao
  • , Xuemin Shen
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we investigate the power allocation in a multi-user wireless system to maximize the energy efficiency, while meeting the power constrains of each individual user and the whole system. Specifically, a geometric ceiled-water-filling algorithm is proposed to solve this non-linear fractional optimization problem, which can compute exact solutions with a low degree of polynomial computational complexity. Optimality of the proposed algorithm is strictly proved with mathematical analysis. In addition, the proposed algorithm is further extended to the general case with the minimum system-level throughput constraint, considering the quality of service requirement. To the best of our knowledge, no prior algorithm in the open literature offered such optimal solutions to the target problems, with the merit of exactness and the efficiency. Simulation results demonstrate that the proposed power allocation algorithms can improve the energy efficiency by nearly 50%, compared with the conventional Dinkelbach's method with the same amount of computations.

Original languageEnglish
Article number8375110
Pages (from-to)5353-5366
Number of pages14
JournalIEEE Transactions on Wireless Communications
Volume17
Issue number8
DOIs
StatePublished - Aug 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Energy efficiency (EE)
  • Exactness
  • Geometric water-filling (GWF)
  • Non-linear fractional optimization
  • Polynomial computational complexity
  • Power allocation

Fingerprint

Dive into the research topics of 'Energy-efficient power allocation with individual and sum power constraints'. Together they form a unique fingerprint.

Cite this