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Record W2057464015 · doi:10.1109/icassp.2010.5496019

Optimal spectrum sharing and power allocation for OFDM-based two-way relaying

2010· article· en· W2057464015 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
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsRelayLinear network codingOrthogonal frequency-division multiplexingComputer sciencePower (physics)Constraint (computer-aided design)Coding (social sciences)Mathematical optimizationDecoding methodsComputer networkOptimization problemMathematicsTelecommunicationsAlgorithmChannel (broadcasting)

Abstract

fetched live from OpenAlex

The problem of optimally allocating power for half-duplex two-way relaying in an OFDM system is considered. Assuming two-way relay is performed using analog network coding, and with total network power constraint, we obtain the optimal power allocation across subcarriers and among a relay and two communicating nodes to maximize the achievable sum rate in the network. We show that the resulting solution is a combination of two (usually opposite) power allocation strategies, i.e., water-filling across subcarriers and SNR-balancing between communicating end nodes. Further analysis also shows the optimal power allocation on the relay itself is a water-filling solution.

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: Methods · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.308

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 science0.0010.000
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 head0.029
GPT teacher head0.287
Teacher spread0.258 · 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