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Record W2121921168 · doi:10.1109/tvt.2007.907029

A Fast Subcarrier, Bit, and Power Allocation Algorithm for Multiuser OFDM-Based Systems

2008· article· en· W2121921168 on OpenAlexaff
Yung‐Fang Chen, Jean-Wei Chen

Bibliographic record

VenueIEEE Transactions on Vehicular Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsPQ Corporation (Canada)
Fundersnot available
KeywordsSubcarrierOrthogonal frequency-division multiplexingBit error rateComputer scienceTransmitter power outputTelecommunications linkAlgorithmBase stationTransmission (telecommunications)Electronic engineeringPower (physics)Channel (broadcasting)Computational complexity theoryReal-time computingTelecommunicationsEngineeringTransmitter

Abstract

fetched live from OpenAlex

In this paper, we propose a real-time subcarrier, bit, and power allocation algorithm for orthogonal frequency-division multiplexing-based multiuser communication systems in downlink transmission. Assuming that base stations know the channel gains of all subcarriers of all users, the proposed loading algorithm tries to minimize the required transmit power while satisfying the rate requirement and data error rate constraint of each user. The novel algorithm simultaneously determines subcarrier, bit, and power allocation by enhancing the suboptimal algorithm by Wong while having the same computational complexity. The proposed scheme offers better performance in terms of transmit power than that of Wong , as demonstrated in the simulation results, whereas the performance of the scheme in Wong was close to that of the optimal solution.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.200
Teacher spread0.193 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Citations52
Published2008
Admission routes1
Has abstractyes

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