Wireless Operators in a Shared Spectrum

Felegyhazi,; Hubaux,

doi:10.1109/infocom.2006.150

Cited by 25 publications

(14 citation statements)

References 21 publications

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“…Respected reference books are [7]. A short overview focusing on the application of game theory in the field of wireless communications can be found in [5].…”

Section: Basics Of Game Theorymentioning

confidence: 99%

“…Keeping this in mind, the original logarithmic utility function u i (prf)=log(r i (prf)) in equation 2 is modified by adding a linear pricing function of the link's prf. The new utility function is given in equation 5.…”

Section: Pulse Rate Control Gamementioning

confidence: 99%

“…Those which can receive on M channels concurrently 4. The power allocation that maximises the sum of the log of source rates, which is a concave objective function 5. When the rate of a link can be approximated by a linear function of the signal-to-interference-and-noise ratio.54 Ultra-Wideband Radio Technologies for Communications, Localization and Sensor Applications Pulse Rate Control for Low Power and Low Data Rate Ultra Wideband Networks…”

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confidence: 99%

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Pulse Rate Control for Low Power and Low Data Rate Ultra Wideband Networks

Guirao¹

2013

Ultra-Wideband Radio Technologies for Communications, Localization and Sensor Applications

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“…Respected reference books are [7]. A short overview focusing on the application of game theory in the field of wireless communications can be found in [5].…”

Section: Basics Of Game Theorymentioning

confidence: 99%

Section: Pulse Rate Control Gamementioning

confidence: 99%

mentioning

confidence: 99%

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Pulse Rate Control for Low Power and Low Data Rate Ultra Wideband Networks

Guirao¹

2013

Ultra-Wideband Radio Technologies for Communications, Localization and Sensor Applications

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“…[18] studies competition for e-services, with also a kind of Wardrop equilibrium, but where QoS does not depend on demand. In other specific contexts, competition between wireless operators in the case of a shared spectrum (more flexible and leading to a more efficient management of the spectrum) has been studied in [19], [20]. In [19], operators are charged by a central entity for the amount of bandwidth they use, and therefore try to design proper service offers for users.…”

Section: A Related Work On Competitionmentioning

confidence: 99%

“…Our analysis is based on a less specific network modeling (and without competition for capacity between providers). In [20], the authors discuss a similar competition problem, but operators only play with the power of the pilot signals of their base stations, and no pricing is considered. On the other hand, note that there is an increasing bunch of works looking at independent and selfish providers on a path, that forward traffic of competitors to ensure end-to-end delivery [21]- [23], but do not consider a direct competition for users between providers, a different perspective that we adopt.…”

Section: A Related Work On Competitionmentioning

confidence: 99%

Analysis of Price Competition in a Slotted Resource Allocation Game

Maillé¹,

Tuffin

2008

IEEE INFOCOM 2008 - The 27th Conference on Computer Communications

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Pricing telecommunication networks has become a highly regarded topic during the last decade, in order to cope with congestion by controlling demand, or to yield proper incentives for a fair sharing of resources. On the other hand, another important factor has to be brought in: there is a rise of competition between service providers in telecommunication networks such as for instance the Internet, and the impact of this competition has to be carefully analyzed. The present paper pertains to this recent stream of works. We consider a slotted resource allocation game with several providers, each of them having a fixed capacity during each time slot, and a fixed access price. Each provider serves its demand up to its capacity, demand in excess being dropped. Total user demand is therefore split among providers according to Wardrop's principle, depending on price and loss probability. Using the characterization of the resulting equilibrium, we prove, under mild conditions, the existence and uniqueness of a Nash equilibrium in the pricing game between providers. We also show that, remarkably, this equilibrium actually corresponds to the socially optimal situation obtained when both users and providers cooperate to maximize the sum of all utilities, this even if providers have the opportunity to artificially reduce their capacity.

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Mathematical Based Models for Group Decision Support in Telecommunication Network Design and Management—Challenges and Trends

Craveirinha

Clímaco

Girão‐Silva

2021

Collective Decisions: Theory, Algorithms and Decision Support Systems

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To the faithful and generous Human Being,To the irreverent and freethinker Citizen, To my dearest friend GregoryJoão * This work is funded by ERDF Funds through the Centre's Regional Operational Program and by National Funds through the FCT -Fundação para a Ciência e a Tecnologia, I.P. under the project CENTRO-01-0145-FEDER-029312. This work was also partially supported by FCT under project UIDB/00308/2020.

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Wireless Operators in a Shared Spectrum

Cited by 25 publications

References 21 publications

Pulse Rate Control for Low Power and Low Data Rate Ultra Wideband Networks

Pulse Rate Control for Low Power and Low Data Rate Ultra Wideband Networks

Analysis of Price Competition in a Slotted Resource Allocation Game

Mathematical Based Models for Group Decision Support in Telecommunication Network Design and Management—Challenges and Trends

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