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Record W2104618250 · doi:10.1109/vetecf.2008.223

Subcarrier, Bit and Power Allocation for Multiuser OFDM-Based Multi-Cell Cognitive Radio Systems

2008· article· en· W2104618250 on OpenAlexaff
Yonghong Zhang, Cyril Leung

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCognitive Radio Networks and Spectrum Sensing
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSubcarrierCognitive radioOrthogonal frequency-division multiplexingComputer scienceKnapsack problemInterference (communication)Greedy algorithmResource allocationFrequency allocationElectronic engineeringComputer networkAlgorithmTelecommunicationsEngineeringWireless

Abstract

fetched live from OpenAlex

We study the subcarrier, bit and power allocation problem for multiuser OFDM-based multi-cell cognitive radio (CR) systems in which one or more spectrum holes exist between multiple primary user (PU) frequency bands. The cognitive radio users (CRUs) are able to share any portion of the frequency band with other CRUs and the PUs as long as this does not interfere unduly with the PUs' transmissions. Both cochannel interference (CI) from other CRUs as well as mutual interference (MI) between the CRUs and the PUs are considered. The resource allocation problem is formulated as a multi-dimensional knapsack problem and a relatively simple, greedy max-min algorithm is proposed to solve it. Simulation results show that the max-min algorithm yields solutions which are close to (within 5% of) optimal. Sharing of the whole band can provide a substantial performance improvement over schemes which use guard bands to protect PU frequency bands and do not allow CRUs to use the PU bands.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.954
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.024
GPT teacher head0.239
Teacher spread0.215 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2008
Admission routes1
Has abstractyes

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