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A General Framework for Wireless
Spectrum Auctions
Advisor ：Wei-Yeh Chen
Student ：楊
于
世

Reference

S. Gandhi , C. Buragohain , L. Cao , H. Zheng and S. Suri , “A
General Framework for Wireless Spectrum Auctions,” in
DySPAN Dublin , pp. 22 - 33 , April 2007.
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Outline

Introduction

Spectrum Auction Framework

Experimental Results

Conclusion
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Introduction(1/2)

We propose a real-time spectrum auction framework
to distribute spectrum among a large number
wireless users under interference constraints.

Our approach achieves conflict-free spectrum
allocations that maximize auction revenue and
spectrum utilization.
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Introduction(2/2)

Our design includes a compact(簡潔地) and yet
highly expressive bidding language, various pricing
models to control tradeoffs between revenue and
fairness, and fast auction clearing algorithms to
compute revenue-maximizing prices and allocations.
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Spectrum Auction Framework
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Price models: Uniform pricing and Discriminatory pricing.
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Spectrum Auction
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Interference Constraint
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Uniform Pricing
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The auctioneer determines a per-unit price and
applies it to all winning bidders.
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The auction clearing problem here is to determine a
market-clearing price that maximizes the auctioneer’s
revenue.
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Discriminatory Pricing
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The auctioneer charges different prices to different
bidders.
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While producing higher financial revenue, this model
is also perceived as less ”fair” to bidders than the
uniform pricing model.
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Spectrum Auction
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There are multiple complementary(互補的) ways to
design spectrum auctions, each applicable(合適的) to
different scenarios.
 The system can allocate/auction transmit power to
minimize interference, while all buyers use the same
spectrum band.
 The system can allocate conflicting users with
orthogonal(直角的) channels to avoid interference.
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Interference Constraint

Spectrum auction differs from conventional(傳統的)
auctions because it has to address radio interference.

Given bids, the problem of auction-clearing becomes
the problem of interference-constrained resource
allocation.
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A dynamic auction scenario. (left) An auctioneer performs
periodic auctions of spectrum to buyers. (right) A conflict graph
illustrates the interference constraints among buyers.
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Node-ALL Interference Constraints

The simplest constraint is to restrict i and every
neighbor of i to use different spectrum channels, i.e.
fi ：頻譜經劃分後的一小單位
N(i)：i的鄰近節點
n：節點總數
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Example network, the conflict graph and the channel
allocations by NI (Node-Interference), NLI (Node-L-Interference),
and OPT (Optimal). There are a total of 5 channels.
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Node-L Interference Constraints(1/3)

We introduce a less restrictive constraint by
imposing(加於) an order among nodes.

By integrating the order in the allocation process, we
can achieve much more efficient allocations than that
using the NI constraints.
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Node-L Interference Constraints(2/3)
fi ：頻譜經劃分後的一小單位
NL(i)：位於i左邊的鄰近節點
n：節點總數
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Node-L Interference Constraints(3/3)

We define the notion of left of. Let two nodes i
and j locate at coordinates (xi, yi) and (xj, yj).

Node i is to the left of node j if xi < xj. If xi
= xj , then the node with the smaller index is
considered to be to the node to the left.
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Experimental Results
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We conduct(引導) experiments to investigate the
performance of the proposed auction framework.
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We plan to examine(檢查) the performance of our
system in planned networks in future work.
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Revenue and spectrum utilization for varying network sizes
for both pricing models.
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Percentage of spectrum allocated to different bidder categories
for uniform (left) and discriminatory (right) pricing models.
CONS/NORM/AGGR: conservative, normal and aggressive bidders.
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Revenue generated by different category bidders for uniform
and discriminatory pricing algorithms.
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Conclusion

這篇論文主要是探討頻譜拍賣的架構，並根據這些架構有
效提供配制頻譜給使用者，讓收入與頻譜的使用能夠達到
最大化，而本篇論文在作法上夾雜許多演算法，以及內容
編排上的規則性讓人看了覺得有點吃力。
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