Fairness-Oriented Resource Allocation for Energy Efficiency Optimization in Uplink OFDMA Networks

Hamza Umit Sokun, Ebrahim Bedeer Mohamed, Ramy Gohary, Halim Yanikomeroglu

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

Abstract—Due to the battery-limited nature of mobile devices, improving energy efficiency (EE) of individual users and ensuring EE fairness among those users are one of the key design issues in uplink transmission of cellular networks. In this paper, we consider the joint optimization of discrete power and resource blocks allocations to maximize the minimum EE among users subject to individual power budget constraints. The optimization problem is combinatorial. Thus, we propose an efficient algorithm, based on semidefinite relaxation with Gaussian randomization, to solve the resultant non-convex problem in polynomial time complexity. The numerical results show how well the proposed algorithm performs against the optimal one and indicate the impact of discrete power levels on the fairness-oriented EE optimization.

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Resource allocation
Energy efficiency
Mobile devices
Polynomials

Keywords

  • Energy efficiency
  • max-min fairness
  • OFDMA
  • convex optimization
  • semidefinite relaxation
  • randomization

Cite this

@article{d9e0163ab70b4c789cf60add23581f09,
title = "Fairness-Oriented Resource Allocation for Energy Efficiency Optimization in Uplink OFDMA Networks",
abstract = "Abstract—Due to the battery-limited nature of mobile devices, improving energy efficiency (EE) of individual users and ensuring EE fairness among those users are one of the key design issues in uplink transmission of cellular networks. In this paper, we consider the joint optimization of discrete power and resource blocks allocations to maximize the minimum EE among users subject to individual power budget constraints. The optimization problem is combinatorial. Thus, we propose an efficient algorithm, based on semidefinite relaxation with Gaussian randomization, to solve the resultant non-convex problem in polynomial time complexity. The numerical results show how well the proposed algorithm performs against the optimal one and indicate the impact of discrete power levels on the fairness-oriented EE optimization.",
keywords = "Energy efficiency, max-min fairness, OFDMA, convex optimization, semidefinite relaxation, randomization",
author = "Sokun, {Hamza Umit} and Mohamed, {Ebrahim Bedeer} and Ramy Gohary and Halim Yanikomeroglu",
year = "2018",
month = "6",
day = "11",
doi = "10.1109/WCNC.2018.8377327",
language = "English",
journal = "2018 IEEE Wireless Communications and Networking Conference (WCNC)",
issn = "1558-2612",

}

Fairness-Oriented Resource Allocation for Energy Efficiency Optimization in Uplink OFDMA Networks. / Sokun, Hamza Umit ; Mohamed, Ebrahim Bedeer; Gohary, Ramy; Yanikomeroglu, Halim.

In: 2018 IEEE Wireless Communications and Networking Conference (WCNC), 11.06.2018.

Research output: Contribution to journalConference article

TY - JOUR

T1 - Fairness-Oriented Resource Allocation for Energy Efficiency Optimization in Uplink OFDMA Networks

AU - Sokun, Hamza Umit

AU - Mohamed, Ebrahim Bedeer

AU - Gohary, Ramy

AU - Yanikomeroglu, Halim

PY - 2018/6/11

Y1 - 2018/6/11

N2 - Abstract—Due to the battery-limited nature of mobile devices, improving energy efficiency (EE) of individual users and ensuring EE fairness among those users are one of the key design issues in uplink transmission of cellular networks. In this paper, we consider the joint optimization of discrete power and resource blocks allocations to maximize the minimum EE among users subject to individual power budget constraints. The optimization problem is combinatorial. Thus, we propose an efficient algorithm, based on semidefinite relaxation with Gaussian randomization, to solve the resultant non-convex problem in polynomial time complexity. The numerical results show how well the proposed algorithm performs against the optimal one and indicate the impact of discrete power levels on the fairness-oriented EE optimization.

AB - Abstract—Due to the battery-limited nature of mobile devices, improving energy efficiency (EE) of individual users and ensuring EE fairness among those users are one of the key design issues in uplink transmission of cellular networks. In this paper, we consider the joint optimization of discrete power and resource blocks allocations to maximize the minimum EE among users subject to individual power budget constraints. The optimization problem is combinatorial. Thus, we propose an efficient algorithm, based on semidefinite relaxation with Gaussian randomization, to solve the resultant non-convex problem in polynomial time complexity. The numerical results show how well the proposed algorithm performs against the optimal one and indicate the impact of discrete power levels on the fairness-oriented EE optimization.

KW - Energy efficiency

KW - max-min fairness

KW - OFDMA

KW - convex optimization

KW - semidefinite relaxation

KW - randomization

U2 - 10.1109/WCNC.2018.8377327

DO - 10.1109/WCNC.2018.8377327

M3 - Conference article

JO - 2018 IEEE Wireless Communications and Networking Conference (WCNC)

T2 - 2018 IEEE Wireless Communications and Networking Conference (WCNC)

JF - 2018 IEEE Wireless Communications and Networking Conference (WCNC)

SN - 1558-2612

ER -