Aligning spectrum-user objectives for maximum inelastic-traffic reward

Bechir Hamdaoui*, Mohammad Javad NoroozOliaee, Kagan Tumer, Ammar Rayes

*Corresponding author for this work

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

4 Citations (Scopus)

Abstract

We develop objective functions for large-scale distributed dynamic spectrum access (DSA) networks that, by means of any learning algorithm, enable DSA users to locate and exploit spectrum opportunities effectively, thereby increasing their achieved throughput (or "rewards" to be more general). We show that the proposed functions are: (i) optimal by enabling users to achieve high rewards, (ii) scalable by performing well in systems with a small as well as a large number of users, (iii) learnable by allowing users to reach up high rewards very quickly, and (iv) distributed by being implementable in a decentralized manner.

Original languageEnglish
Title of host publication2011 20th International Conference on Computer Communications and Networks, ICCCN 2011 - Proceedings
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 20th International Conference on Computer Communications and Networks, ICCCN 2011 - Maui, HI, United States
Duration: 31 Jul 20114 Aug 2011

Publication series

NameProceedings - International Conference on Computer Communications and Networks, ICCCN
ISSN (Print)1095-2055

Conference

Conference2011 20th International Conference on Computer Communications and Networks, ICCCN 2011
Country/TerritoryUnited States
CityMaui, HI
Period31/07/114/08/11

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