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Record W2160880670 · doi:10.1109/icccn.2007.4317788

A New Perspective of Cross-layer Optimization for Wireless Communication over Fading Channel

2007· article· en· W2160880670 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 institutionsWestern University
Fundersnot available
KeywordsComputer scienceCross-layer optimizationFadingLink adaptationPhysical layerQueueing theoryTransmission (telecommunications)Optimization problemChannel (broadcasting)Network packetComputer networkWirelessCoding (social sciences)AlgorithmWireless networkTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

In most designed adaptive modulation and coding (AMC) schemes the data link layer transmission rate is adapted only against physical layer channel variation. The highly fluctuating queuing process at the data link layer is not fully investigated. In this study, we first research on more advanced AMC mode selection algorithms and then propose a two-dimensional cross- layer optimization scheme. This scheme applies both policy domain optimization and channel domain improvement to achieve the best solution. With the same transmission power, the proposed two-dimensional optimization scheme is shown to be capable of offering lower minimum end-to-end packet loss probability than the existing one-dimensional optimization design.

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 score0.777
Threshold uncertainty score0.565

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 head0.016
GPT teacher head0.295
Teacher spread0.279 · 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

Citations3
Published2007
Admission routes1
Has abstractyes

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