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Record W2033311501 · doi:10.1109/ahici.2011.6113934

Joint power and subcarrier allocation in multi-hop OFDMA network: A cross-layer approach

2011· article· en· W2033311501 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 institutionsUniversity of British Columbia
Fundersnot available
KeywordsGoodputComputer scienceComputer networkSubcarrierOrthogonal frequency-division multiple accessNetwork packetHop (telecommunications)Frequency-division multiple accessWireless networkTransmitter power outputResource allocationPhysical layerWirelessOrthogonal frequency-division multiplexingTelecommunicationsThroughputChannel (broadcasting)Transmitter

Abstract

fetched live from OpenAlex

Resource wastage due to loss of a packet in a multi-hop wireless network greatly depends on number of hops the packet has already traveled. Hence, consideration of hop-count information is crucial while optimizing overall resource utilization of such network. Therefore, we propose a cross-layer resource allocation approach for an orthogonal frequency division multiple access based multi-hop network which jointly allocates subcarriers and transmit power prioritizing packets with higher hop-counts. Simulation results show that the proposed scheme is capable of minimizing network-wide resource wastage significantly without degradation in goodput and system outage performance.

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: Empirical · Consensus signal: none
Teacher disagreement score0.693
Threshold uncertainty score0.610

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 head0.039
GPT teacher head0.243
Teacher spread0.204 · 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
Published2011
Admission routes1
Has abstractyes

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