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Record W1996831548 · doi:10.1109/infcom.2010.5462277

A Secondary Market for Spectrum

2010· article· en· W1996831548 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicAuction Theory and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCommon value auctionVariation (astronomy)Supply and demandBandwidth (computing)Market mechanismComputer scienceSpectrum auctionStock marketChannel (broadcasting)Secondary marketCognitive radioSpectrum (functional analysis)Stock (firearms)Industrial organizationMicroeconomicsTelecommunicationsBusinessEconomicsWirelessStock exchangeEngineeringMarket economyAuction theoryFinance

Abstract

fetched live from OpenAlex

Dynamic spectrum trading amongst small cognitive users is fundamentally different along two axes: temporal variation, and spatial variation of user demand and channel condition. We advocate that a spectrum secondary market, analogous to the stock market, is to be established for users to dynamically trade among themselves their channel holdings obtained in the primary market from legacy owners. We design a market mechanism based on dynamic double auctions, creating a marketplace in the air to match bandwidth demand with supply. In the analysis we prove important economic properties of the mechanism, notably its truthfulness and asymptotic efficiency in maximizing spectrum utilization. Complimentary simulation studies corroborate that spectrum utilization and user performance can be improved by establishing the spectrum secondary market.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.755
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0500.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.385
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations96
Published2010
Admission routes1
Has abstractyes

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