DocumentCode :
1680801
Title :
Collusion-Resistant Multi-Winner Spectrum Auction for Cognitive Radio Networks
Author :
Yongle Wu ; Beibei Wang ; Liu, K.J.R. ; Clancy, T. Charles
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA
fYear :
2008
Firstpage :
1
Lastpage :
5
Abstract :
In order to fully utilize spectrum, auction-based dynamic spectrum allocation has become a promising approach which allows unlicensed wireless users to lease unused bands from spectrum license holders. Because spectrum resources are reusable by users far apart, in some scenarios, spectrum is more efficiently utilized by awarding one band to multiple secondary users simultaneously, which distinguishes it from traditional auctions where only one user can be the winner. However, the multi-winner auction is a new concept posing new challenges in the traditional auction mechanisms, because such mechanisms may yield low revenue and are not robust to some newly-emerging collusion. Therefore, in this paper, we propose an efficient mechanism for the multi-winner spectrum auction with collusion- resistant pricing strategies, in which the optimal spectrum allocation can be solved by binary linear programming and the pricing is formulated as a convex optimization problem. Furthermore, a greedy algorithm is proposed to reduce complexity for multi- band auctions. Simulation results are presented to evaluate our proposed auction mechanisms.
Keywords :
bandwidth allocation; cognitive radio; linear programming; pricing; radio networks; binary linear programming; cognitive radio networks; collusion-resistant pricing strategies; convex optimization; multi-winner spectrum auction; spectrum allocation; spectrum resources; Cognitive radio; Educational institutions; FCC; Greedy algorithms; Interference; Laboratories; Licenses; Linear programming; Pricing; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Global Telecommunications Conference, 2008. IEEE GLOBECOM 2008. IEEE
Conference_Location :
New Orleans, LO
ISSN :
1930-529X
Print_ISBN :
978-1-4244-2324-8
Type :
conf
DOI :
10.1109/GLOCOM.2008.ECP.597
Filename :
4698372
Link To Document :
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