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Record W3187112037 · doi:10.1109/lwc.2021.3102189

Downlink Multi-Carrier NOMA With Opportunistic Bandwidth Allocations

2021· article· en· W3187112037 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 · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Technologies
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsNomaBandwidth (computing)Computer scienceTelecommunications linkBandwidth allocationConvexityDynamic bandwidth allocationWirelessComputer networkMaximizationWireless networkMathematical optimizationTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

Multi-carrier non-orthogonal multiple access (MC-NOMA) system has been considered as a promising candidate in future wireless networks. In a MC-NOMA system, the available bandwidth of transmission is divided into several sub-bands, such that multiple users in each sub-band are served based on power-domain NOMA. Unlike the equal sub-band allocations, we propose a sum-rate maximization technique that jointly allocates the available power and bandwidth with opportunistic sharing between the sub-bands. A second-order cone program approach is exploited to deal with the non-convexity issues of the corresponding optimization problem. Simulation results reveal that the MC-NOMA system with opportunistic bandwidth allocation outperforms the scheme with the equal bandwidth allocation in terms of achieved sum-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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.793
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.034
GPT teacher head0.254
Teacher spread0.220 · 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