JOURNAL ARTICLE

Collusion-Resistant Multi-Winner Spectrum Auction for Cognitive Radio Networks

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:
Spectrum auction Computer science Collusion Cognitive radio Combinatorial auction Auction theory Frequency allocation Common value auction Mathematical optimization Greedy algorithm Auction algorithm Spectrum management Optimization problem Generalized second-price auction Revenue Revenue equivalence Wireless Computer network Microeconomics Telecommunications Algorithm Business Economics

Metrics

38
Cited By
6.28
FWCI (Field Weighted Citation Impact)
17
Refs
0.97
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Auction Theory and Applications
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Cognitive Radio Networks and Spectrum Sensing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Supply Chain and Inventory Management
Social Sciences →  Business, Management and Accounting →  Management Information Systems
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