A Game Theoretic Approach to Spectrum Pricing in Two-Tier HetNets with Incomplete Information

Andrea Guevara Toledo, Sofie Pollin, Alessandro Chiumento

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

106 Downloads (Pure)

Abstract

This paper studies a scenario as an oligopolistic game in an cognitive radio market where primary networks compete with each other to obtain a maximum profit by selling unused spectrum. Assuming that one of the primary networks does not provide information about the amount of available spectrum for the auction, a Bertrand game with incomplete information is used as a model for this market. A Nash Bayesian Game is proposed as a solution, which achieves an equilibrium for the profit earned by both primary networks. In this game the cost, demand and profit are functions of spectral efficiency and spectrum substitutability, which enables us to analyse their impact on the market. As a result of this work we conclude that a secondary network will choose the cheapest spectrum price in the market regardless the QoS offered by a primary network. However when the market is very competitive there is an uncertain behaviour in the network due the lack of information provided for one of the primary networks. This is measured as a 1.4dB quality of service range where it is not certain that the lowest price will win.
Original languageEnglish
Title of host publicationSymposium on Information Theory and Signal Processing in the Benelux
Pages67-70
Publication statusPublished - 2017
Externally publishedYes
Event38th Symposium on Information Theory and Signal Processing in the Benelux 2017 - Delft University of Technology, Delft, Netherlands
Duration: 11 May 201712 May 2017
Conference number: 38

Conference

Conference38th Symposium on Information Theory and Signal Processing in the Benelux 2017
CountryNetherlands
CityDelft
Period11/05/1712/05/17

Fingerprint

Dive into the research topics of 'A Game Theoretic Approach to Spectrum Pricing in Two-Tier HetNets with Incomplete Information'. Together they form a unique fingerprint.

Cite this