Mobile Data Offloading with Uniform Pricing and Overlaps

Mingmei Li, Tony Q.S. Quek, Costas Courcoubetis

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


Mobile data offloading is an emerging technology to alleviate cellular network congestion and improve user service quality. In this paper, we investigate the economics of mobile data offloading through access points (APs) deployed by small cell service providers (SSPs), implementing uniform volume prices for all the mobile users (MUs) in each SSP's coverage including the overlapping area. In particular, we consider a data offloading game with a single mobile network operator (MNO) and two SSPs with overlapping coverage areas, where each SSP announces a uniform price for serving the cellular traffic within its coverage, and the MNO determines the traffic volumes to offload. We show that there is no pure Nash equilibrium (PNE) under such price competition, and determine the corresponding mixed strategy Nash equilibrium (MNE) using price randomization. As a practical solution, we propose a simple one shot auction mechanism that is easy to implement and has PNEs which is payoff equivalent with the MNE under price competition. We believe that this simple mechanism due to its simplicity of determining the equilibrium prices could be used in the negotiation between the SSPs and the MNO to determine the average service prices. Finally, we study the strategic topological infrastructure placement problem using a 1-dimension (1D, linear) user traffic flow model and a 2-dimension (2D) user traffic flow model when SSPs compete assuming uniform price competition as above. We show that the first mover in the placement problem will deploy its APs to cover more than half of the total flow volume and has an advantage to obtain a higher equilibrium payoff.

Original languageEnglish
Article number8361073
Pages (from-to)348-361
Number of pages14
JournalIEEE Transactions on Mobile Computing
Issue number2
Publication statusPublished - 2019 Feb 1

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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