The University of Southampton
University of Southampton Institutional Repository

Energy efficient OFDMA networks maintaining statistical QoS guarantees for delay-sensitive traffic

Energy efficient OFDMA networks maintaining statistical QoS guarantees for delay-sensitive traffic
Energy efficient OFDMA networks maintaining statistical QoS guarantees for delay-sensitive traffic
An energy-efficient design is proposed under specific statistical quality-of-service (QoS) guarantees for delay-sensitive traffic in the downlink orthogonal frequency-division multiple access (OFDMA) networks. This design is based on Wu’s effective capacity (EC) concept [1], which characterizes the maximum throughput of a system subject to statistical delay-QoS requirements at the data-link layer. In the particular context considered, our main contributions consist of quantifying the effective energy-efficiency (EEE)-versus-EC tradeoff and characterizing the delay sensitive traffic as a function of the QoS-exponent ?, which expresses the exponential decay rate of the delay-QoS violation probabilities. Upon exploiting the properties of fractional programming, the originally quasi-concave EEE optimization problem having a fractional form is transformed into a subtractive optimization problem by applying Dinkelbach’s method. As a result, an iterative inner-outer loop based resource allocation algorithm is conceived for efficiently solving the transformed EEE optimization problem. Our simulation results demonstrate that the proposed scheme converges within a few Dinkelbach iterations to the desired solution accuracy. Furthermore, the impact of the circuitry power, of the QoS-exponent and of the power amplifier inefficiency is characterized numerically. These results reveal that the optimally allocated power maximizing the EEE decays exponentially with respect to both the circuitry power and the QoS-exponent, whilst decaying linearly with respect to the power amplifier inefficiency.
5G, effective energy-efficiency (EEE), statistical quality-of-service (QoS), delay-sensitive traffic, Dinkelbach’s method, effective capacity, orthogonal frequency-division multiple-access (OFDMA)
774-791
Abrão, Taufik
d61b626e-49e3-493b-a88f-99b239e1a028
Sampaio, Lucas D. H.
959a1f96-bf24-448b-a064-0242910a99dc
Yang, Shaoshi
df1e6c38-ff3b-473e-b36b-4820db908e60
Cheung, Kent Tsz Kan
77118f8f-b4ed-4e01-a747-9bb3a3809ad8
Jeszensky, Paul Jean Etienne
6d6188e2-d497-429d-be6e-b9cb06d350ac
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Abrão, Taufik
d61b626e-49e3-493b-a88f-99b239e1a028
Sampaio, Lucas D. H.
959a1f96-bf24-448b-a064-0242910a99dc
Yang, Shaoshi
df1e6c38-ff3b-473e-b36b-4820db908e60
Cheung, Kent Tsz Kan
77118f8f-b4ed-4e01-a747-9bb3a3809ad8
Jeszensky, Paul Jean Etienne
6d6188e2-d497-429d-be6e-b9cb06d350ac
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Abrão, Taufik, Sampaio, Lucas D. H., Yang, Shaoshi, Cheung, Kent Tsz Kan, Jeszensky, Paul Jean Etienne and Hanzo, Lajos (2016) Energy efficient OFDMA networks maintaining statistical QoS guarantees for delay-sensitive traffic. IEEE Access, 4, 774-791. (doi:10.1109/ACCESS.2016.2530688).

Record type: Article

Abstract

An energy-efficient design is proposed under specific statistical quality-of-service (QoS) guarantees for delay-sensitive traffic in the downlink orthogonal frequency-division multiple access (OFDMA) networks. This design is based on Wu’s effective capacity (EC) concept [1], which characterizes the maximum throughput of a system subject to statistical delay-QoS requirements at the data-link layer. In the particular context considered, our main contributions consist of quantifying the effective energy-efficiency (EEE)-versus-EC tradeoff and characterizing the delay sensitive traffic as a function of the QoS-exponent ?, which expresses the exponential decay rate of the delay-QoS violation probabilities. Upon exploiting the properties of fractional programming, the originally quasi-concave EEE optimization problem having a fractional form is transformed into a subtractive optimization problem by applying Dinkelbach’s method. As a result, an iterative inner-outer loop based resource allocation algorithm is conceived for efficiently solving the transformed EEE optimization problem. Our simulation results demonstrate that the proposed scheme converges within a few Dinkelbach iterations to the desired solution accuracy. Furthermore, the impact of the circuitry power, of the QoS-exponent and of the power amplifier inefficiency is characterized numerically. These results reveal that the optimally allocated power maximizing the EEE decays exponentially with respect to both the circuitry power and the QoS-exponent, whilst decaying linearly with respect to the power amplifier inefficiency.

Text
07407606.pdf - Version of Record
Restricted to Repository staff only
Request a copy

More information

Published date: 16 February 2016
Keywords: 5G, effective energy-efficiency (EEE), statistical quality-of-service (QoS), delay-sensitive traffic, Dinkelbach’s method, effective capacity, orthogonal frequency-division multiple-access (OFDMA)
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 386735
URI: https://eprints.soton.ac.uk/id/eprint/386735
PURE UUID: dfafb7c4-4f68-4395-aeb8-a2916abfbc83
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 03 Feb 2016 16:18
Last modified: 15 Aug 2019 00:57

Export record

Altmetrics

Contributors

Author: Taufik Abrão
Author: Lucas D. H. Sampaio
Author: Shaoshi Yang
Author: Kent Tsz Kan Cheung
Author: Paul Jean Etienne Jeszensky
Author: Lajos Hanzo ORCID iD

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×