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Record W2972917489 · doi:10.1109/lwc.2019.2940942

Contract Design for Time Resource Assignment and Pricing in Backscatter-Assisted RF-Powered Networks

2019· article· en· W2972917489 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

VenueIEEE Wireless Communications Letters · 2019
Typearticle
Languageen
FieldEngineering
TopicEnergy Harvesting in Wireless Networks
Canadian institutionsYork University
FundersNational Natural Science Foundation of ChinaMinistry of Education - Singapore
KeywordsComputer scienceGateway (web page)Default gatewayIncentiveProfit (economics)Computer networkTransmitterBackscatter (email)TelecommunicationsOperations researchWirelessEconomicsMicroeconomicsEngineering

Abstract

fetched live from OpenAlex

Backscatter communication has been acknowledged as an essential supplement to improve the performance of radio-frequency-powered networks. Considering the fact that the backscatter communication needs the cooperation from the secondary gateway, pricing is an effective method to incentivize the secondary gateway to take part in the backscatter communication. In this letter, we consider a practical scenario, where the secondary gateway only knows the statistical information about the harvested power of the secondary transmitter, and develop a time resource assignment and pricing scheme for the network based on contract theory. Specifically, the secondary gateway designs a contract, including a series of time-price items, to maximize its profit. Then, the secondary transmitter accepts the contract item which can maximize its utility. We derive the optimal contract, which guarantees the incentive compatibility and the individual rationality properties. Numerical results are presented to verify the effectiveness of our designed contract.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.224
Teacher spread0.207 · 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