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Record W2315852694 · doi:10.1109/lcomm.2016.2544830

Power Allocation for SC-FDE-Based CR Systems Under Explicit Primary User Protection

2016· article· en· W2315852694 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 Communications Letters · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Network Optimization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTransmitterMaximizationMathematical optimizationConstraint (computer-aided design)Transmitter power outputComputer sciencePower (physics)Max-min fairnessConvex optimizationOptimization problemRegular polygonResource allocationMathematicsTelecommunicationsComputer network

Abstract

fetched live from OpenAlex

In this letter, we consider the power allocation for a single-carrier (SC)-based secondary user (SU) transmitter (Tx), which transmits concurrently with an SC or multicarrier (MC) primary user (PU) over the same frequency band. A rate maximization problem for the SU system is formulated subject to an SU-Tx power constraint and an explicit rate loss constraint for the PU system. Due to the nonconvexity of the resulting problem, we propose a successive convex approximation approach to solve the problem where in each iteration closed-form solutions are derived for the power allocation variables of the SU-Tx. We further prove that the proposed algorithm is guaranteed to converge to a local optimum of the original nonconvex problem. Simulation results are provided to show the efficacy of the proposed approach.

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 score0.958
Threshold uncertainty score0.650

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 head0.024
GPT teacher head0.231
Teacher spread0.207 · 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