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Record W2101132792 · doi:10.1109/icassp.2008.4518335

Joint power and resource allocation for orthogonal amplify-and-forward pairwise user cooperation

2008· article· en· W2101132792 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

VenueProceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing · 2008
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsMcMaster University
Fundersnot available
KeywordsResource allocationPairwise comparisonComputer scienceMathematical optimizationMax-min fairnessChannel (broadcasting)Channel allocation schemesBandwidth (computing)Resource management (computing)Joint (building)Transmission (telecommunications)Power (physics)Computer networkWirelessTelecommunicationsMathematicsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

We consider the jointly optimal allocation of transmission power and channel resources (such as time and bandwidth) for an orthogonal amplify-and-forward (AF) pairwise cooperation scheme. In particular, we derive a simple efficient algorithm for determining the joint allocations required to operate at any point on the boundary of the achievable rate region. The algorithm is based on a closed-form solution, derived herein, for the optimal power allocation for a given channel resource allocation, and on showing that the channel resource allocation problem is quasi-convex.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.959
Threshold uncertainty score0.568

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 communication0.0000.001
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 head0.067
GPT teacher head0.286
Teacher spread0.218 · 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