Published September 10, 2013
| Version v1
Conference paper
A game theoretic approach for the association problem in two-tier HetNets
Contributors
Others:
- Models for the performance analysis and the control of networks (MAESTRO) ; Centre Inria d'Université Côte d'Azur (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- Institute of Mathematics and Computer Science [Wroclaw] (IMCS) ; Wroclaw University of Science and Technology
- Laboratoire Informatique d'Avignon (LIA) ; Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI
Description
This paper addresses a Bayesian game theoretic framework for determining the association rules that decide to which cell a given mobile user should associate in LTE two-tier Heterogeneous Networks (HetNets). Users are assumed to compete to maximize their throughput by picking the best locally serving cell with respect to their own measurement, their demand and a partial statistical channel state information (CSI) of other users. In particular, we investigate the properties of a hierarchical game, in which the macro-cell BS is a player on its own. We derive analytically the utilities related to the channel quality perceived by users to obtain the equilibria. We show by means of a Stackelberg formulation, how the operator, by dynamically choosing the offset about the state of the channel, can optimize its global utility while end-users maximize their individual utilities. The proposed hierarchical decision approach for wireless networks can reach a good trade-off between the global network performance at the equilibrium and the requested amount of signaling. Typically, it is shown that when the network goal is orthogonal to user's goal, this can lead the users to a misleading association problem. Numerical results validate the expectation from the theoretical analysis and illustrate the advantages of the proposed approach.
Abstract
International audienceAdditional details
Identifiers
- URL
- https://inria.hal.science/hal-00913200
- URN
- urn:oai:HAL:hal-00913200v1
Origin repository
- Origin repository
- UNICA