An Analytical Framework for Effective Joint Scheduling over TDD-Based Mobile Networks

Issam W. Damaj*, Ahmad M. El Hajj, Hussein T. Mouftah

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

The growing demand for data along with the emergence of new communication standards have reshaped wireless networks through a denser base station deployment, an increasing traffic heterogeneity, and an additional complexity in quality of service (QoS) assurance. Orthogonal Frequency Division Multiple Access (OFDMA) is considered as one technique to be used in next generation wireless networks. Utilizing time division duplexing (TDD) aids the management of resources and providing effective QoS. In the literature, common approaches in assessing effectiveness attempt to capture performance using single indicators that reflect one aspect of the network's operation. consequently, multi-objective evaluations are not easy and require intuitively considering isolated descriptions, plots, visualizations, and holistically performing multiple comparisons. In this paper, we propose an analytical framework that aims to classify the effectiveness of joint scheduling algorithms over TDD-OFDMA networks per combined heterogeneous properties. In the suggested framework, a designer benefits from a bouquet of carefully customized indicators that can lead to quality evaluations, performance classifications beyond traditional approaches, and accurate improvements. Validation includes exhaustive simulations and the assessment of different scheduling and performance classification schemes. The obtained results confirm the validity of the framework and confirms its effectiveness in application.

Original languageEnglish
Article number8861041
Pages (from-to)144214-144229
Number of pages16
JournalIEEE Access
Volume7
DOIs
Publication statusPublished - 7 Oct 2019
Externally publishedYes

Keywords

  • Performance
  • classification
  • joint scheduling
  • mobile networks
  • networks

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