Generalized gradient scheduling for vector network utility maximization

Heejin Joung, Han Shin Jo, Cheol Mun, Jong Gwan Yook

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Generalized network utility maximization (NUM), which has a multiple-variable vector utility function, is a key framework in network resource allocation that supports multi-class services with a different efficiency and fairness. We propose a generalized gradient scheduling (GS) that easily finds a solution to the generalized NUM problem by simplifying its objective function. The properties of the argument of the maximum and the directional derivative are applied to the simplification process. Achieving a generalized GS is a necessary condition for achieving a generalized NUM, and for a special case with scalar utility functions, the generalized GS and generalized NUM are equivalent problems. A practical application of the findings to uplink cellular networks is also presented in this paper.

Original languageEnglish
Article number6397542
Pages (from-to)111-114
Number of pages4
JournalIEEE Communications Letters
Volume17
Issue number1
DOIs
Publication statusPublished - 2013 Jan 4

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Utility Maximization
Generalized Gradient
Scheduling
Utility Function
Directional derivative
Resource allocation
Uplink
Multi-class
Cellular Networks
Fairness
Resource Allocation
Simplification
Derivatives
Objective function
Scalar
Necessary Conditions

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Joung, Heejin ; Jo, Han Shin ; Mun, Cheol ; Yook, Jong Gwan. / Generalized gradient scheduling for vector network utility maximization. In: IEEE Communications Letters. 2013 ; Vol. 17, No. 1. pp. 111-114.
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Generalized gradient scheduling for vector network utility maximization. / Joung, Heejin; Jo, Han Shin; Mun, Cheol; Yook, Jong Gwan.

In: IEEE Communications Letters, Vol. 17, No. 1, 6397542, 04.01.2013, p. 111-114.

Research output: Contribution to journalArticle

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