Vidal's libraryTitle: | Auction-Based Spectrum Sharing |
Author: | Jianwei Huang, Randall A. Berry, and Michael L. Honig |
Journal: | Mobile Networks and Applications |
Volume: | 11 |
Pages: | 405--418 |
Year: | 2006 |
DOI: | 10.1007/s11036-006-5192-y |
Abstract: | We study auction mechanisms for sharing spectrum among a group of users, subject to a constraint on the interference temperature at a measurement point. The users access the channel using spread spectrum signaling and so interfere with each other. Each user receives a utility that is a function of the received signal-to-interference plus noise ratio. We propose two auction mechanisms for allocating the received power. The first is an auction in which users are charged for received SINR, which, when combined with logarithmic utilities, leads to a weighted max-min fair SINR allocation. The second is an auction in which users are charged for power, whichmaximizes the total utility when the bandwidth is large enough and the receivers are co-located. Both auction mechanisms are shown to be socially optimal for a limiting “large system” with co-located receivers, where bandwidth, power and the number of users are increased in fixed proportion. We also formulate an iterative and distributed bid updating algorithm, and specify conditions under which this algorithm converges globally to the Nash equilibrium of the auction. |
Cited by 12 - Google Scholar
@Article{huang06a,
author = {Jianwei Huang and Randall A. Berry and Michael
L. Honig},
title = {Auction-Based Spectrum Sharing},
journal = {Mobile Networks and Applications},
year = 2006,
volume = 11,
pages = {405--418},
abstract = {We study auction mechanisms for sharing spectrum
among a group of users, subject to a constraint on
the interference temperature at a measurement
point. The users access the channel using spread
spectrum signaling and so interfere with each
other. Each user receives a utility that is a
function of the received signal-to-interference plus
noise ratio. We propose two auction mechanisms for
allocating the received power. The first is an
auction in which users are charged for received
SINR, which, when combined with logarithmic
utilities, leads to a weighted max-min fair SINR
allocation. The second is an auction in which users
are charged for power, whichmaximizes the total
utility when the bandwidth is large enough and the
receivers are co-located. Both auction mechanisms
are shown to be socially optimal for a limiting
``large system'' with co-located receivers, where
bandwidth, power and the number of users are
increased in fixed proportion. We also formulate an
iterative and distributed bid updating algorithm,
and specify conditions under which this algorithm
converges globally to the Nash equilibrium of the
auction.},
url = {http://jmvidal.cse.sc.edu/library/huang06a.pdf},
doi = {10.1007/s11036-006-5192-y},
keywords = {game-theory networks auctions},
cluster = {15126197676409315995}
}
Last modified: Wed Mar 9 10:16:38 EST 2011