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Record W2115774703 · doi:10.1109/icbn.2005.1589642

Adaptive BCPM downlink resource allocation strategies for multiuser OFDM in cellular systems

2005· article· en· W2115774703 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
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsMcGill University
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingTelecommunications linkComputer scienceFadingBandwidth (computing)Resource allocationTransmission (telecommunications)Network packetBandwidth allocationMinificationInterference (communication)Computer networkElectronic engineeringMathematical optimizationTelecommunicationsMathematicsEngineeringChannel (broadcasting)

Abstract

fetched live from OpenAlex

This paper presents an adaptive downlink resource allocation strategy for multi-user orthogonal frequency division multiplexing (OFDM) cellular systems, which minimizes first the transmission bandwidth and then the transmission power. By analysis, it is shown that by keeping the minimum numbers of allocated sub-carriers to satisfy user rate requirements, the probability of interference occurrence in the sub-carriers is reduced and improves the expected link outage probability in the presence of flat fading and shadowing. The proposed bandwidth-constrained power minimization (BCPM) problem is formulated as a linear programming problem and used to derive three-step BCPM schemes. Simulation results in a cellular system to support voice and data services in presence of both frequency selective fading and shadowing show that the proposed BCPM schemes outperform the power minimization (PM) in terms of system outage and packet error rate.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.945
Threshold uncertainty score0.562

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 head0.011
GPT teacher head0.211
Teacher spread0.200 · 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

Citations5
Published2005
Admission routes1
Has abstractyes

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