Algorithmic Game Theory
eBay in the Sky: strategy-proof wireless spectrum auctions
Proceedings of the 14th ACM international conference on Mobile computing and networking
A secondary market for spectrum
INFOCOM'10 Proceedings of the 29th conference on Information communications
SALSA: Strategyproof Online Spectrum Admissions for Wireless Networks
IEEE Transactions on Computers
Efficient and Strategyproof Spectrum Allocations in Multichannel Wireless Networks
IEEE Transactions on Computers
TOFU: semi-truthful online frequency allocation mechanism for wireless network
IEEE/ACM Transactions on Networking (TON)
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In this work, we study spectrum auction problem where each spectrum usage request has spatial, temporal, and spectral features. After receiving bid requests from secondary users, and possibly reserve price from primary users, our goal is to design truthful mechanisms that will either optimize the social efficiency or optimize the revenue of the primary user. As computing an optimal conflict-free spectrum allocation is an NP-hard problem, in this work, we design near optimal spectrum allocation mechanisms separately based on the techniques: derandomized allocation from integer programming formulation, and its linear programming (LP) relaxation. We theoretically prove that 1) our derandomized allocation methods are monotone, thus, implying truthful auction mechanisms; 2) our derandomized allocation methods can achieve a social efficiency or a revenue that is at least $1-\frac{1}{e}$ times of the optimal respectively; Our extensive simulation results corroborate our theoretical analysis.