To accommodate the soaring mobile
broadband traffic, the Federal Communications Commission (FCC) in the U.S. sets
out to retrieve under-utilized spectrum (e.g., TV Whitespace) and lay the
groundwork for spectrum redistribution. Auction is an efficient way to allocate
resources to those who value them the most. The large pool of spectrums to be
released, especially the ones in TV Whitespace, consist of wide-range
frequencies. Apart from spatial reuse, spectrum heterogeneity imposes new
challenges for spectrum auction design 1) Wireless service providers with
different targeted cell coverages have different spectrum frequency
preferences; 2) Interference relationship is frequency dependent due to
frequency-selective signal fading. Unfortunately, existing spectrum auction
mechanisms either assume spectrum valuation is homogeneous or use homogeneous
interference graph to group buyers who can reuse the same spectrum. In this
paper, we propose TAMES, an auction framework for heterogeneous spectrum
transaction. We consider a multi-seller-multi-buyer double auction, in which
every buyer submits a bid, consisting of the spectrum demand and a bidding
profile of prices for spectrums contributed by all sellers. A novel buyer
grouping approach is proposed to tackle the problem of heterogeneous
interference graph. TAMES is proved to be truthful as well as individually
rational. The simulation results show that TAMES significantly improves
spectrum utilization, sellers' revenue and buyers' utility by making smart use
of spectrum heterogeneity. The running time of TAMES linearly increases with
the number of auction participants. Moreover, via simulation, we show how to
help buyers obtain continuous spectrums which further improves buyers'
satisfaction.
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