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Dynamic Spectrum Management for WCDMA/DVB Heterogeneous Systems

2011· article· en· W2078834394 on OpenAlexaff
Zhiyong Feng, Wei Li, Qian Li, Vanbin Le, T. Aaron Gulliver

Bibliographic record

VenueIEEE Transactions on Wireless Communications · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer scienceDigital Video BroadcastingCode division multiple accessBroadcasting (networking)Frequency allocationSpread spectrumComputer networkScheme (mathematics)Spectrum managementDigital televisionWirelessTelecommunicationsCognitive radioMathematics

Abstract

fetched live from OpenAlex

This paper proposes a novel Dynamic Spectrum Management (DSM) scheme for Wideband Code Division Multiple Access (WCDMA) / Digital Video Broadcasting (DVB) heterogeneous systems. Capacity estimation algorithms for both WCDMA and DVB are developed which consider both the user distribution and characteristics of the hybrid services. Based on these algorithms, a new dynamic spectrum allocation scheme is presented which allows for optimum allocation of resources and maximum secondary spectrum usage. Coloring theory is used to significantly reduce DSM complexity while providing near-optimal performance. Numerical results are given which show that the proposed DSM scheme has better performance than Fixed Spectrum Management (FSM).

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.023
GPT teacher head0.237
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 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
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
Published2011
Admission routes1
Has abstractyes

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