Pricing Mobile Data Offloading: A Distributed Market Framework

Kehao Wang, Chung Ming Lau, Lin Chen, Robert Schober

Research output: Journal article publicationJournal articleAcademic researchpeer-review

38 Citations (Scopus)

Abstract

Mobile data offloading is an emerging technology to avoid congestion in cellular networks and improve the level of user satisfaction. In this paper, we develop a distributed market framework to price the offloading service, and conduct a detailed analysis of the incentives for offloading service providers and conflicts arising from the interactions of different participators. Specifically, we formulate a multileader multifollower Stackelberg game (MLMF-SG) to model the interactions between the offloading service providers and the offloading service consumers in the considered market framework, and investigate the cases where the offloading capacity of APs is unlimited and limited, respectively. For the case without capacity limit, we decompose the followers' game of the MLMF-SG (FG-MLMF-SG) into a number of simple follower games (FGs), and prove the existence and uniqueness of the equilibrium of the FGs from which the existence and uniqueness of the FG-MLMF-SG also follows. For the leaders' game of the MLMF-SG, we also prove the existence and uniqueness of the equilibrium. For the case with capacity limit, by considering a symmetric strategy profile, we establish the existence and uniqueness of the equilibrium of the corresponding MLMF-SG, and present a distributed algorithm that allows the leaders to achieve the equilibrium. Finally, extensive numerical experiments demonstrate that the Stackelberg equilibrium is very close to the corresponding social optimum for both considered cases.
Original languageEnglish
Article number7275166
Pages (from-to)913-927
Number of pages15
JournalIEEE Transactions on Wireless Communications
Volume15
Issue number2
DOIs
Publication statusPublished - 1 Feb 2016

Keywords

  • Mobile Traffic Offloading
  • Nash Equilibrium
  • Stackelberg Game
  • WiFi Offloading

ASJC Scopus subject areas

  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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