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Record W2172082297 · doi:10.1109/tmtt.2011.2166977

Behavioral Modeling of MIMO Nonlinear Systems With Multivariable Polynomials

2011· article· en· W2172082297 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 Transactions on Microwave Theory and Techniques · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMIMOMultivariable calculusNonlinear systemControl theory (sociology)AmplifierBehavioral modelingPolynomialElectronic engineeringWirelessComputer scienceTransmitterRadio frequencyRF power amplifierChannel (broadcasting)MathematicsEngineeringControl engineeringTelecommunicationsPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

This paper proposes a novel behavioral model for multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) nonlinear transmitters based on multivariable polynomials (MVPs). The main source of nonlinearity in these transmitters is the RF power amplifier, which is commonly modeled using polynomial models. The proposed MVP model is capable of handling the nonlinear effects of the RF transmitters, as well as the linear and nonlinear crosstalk between the input signals. At the same time, the developed model was optimized for computing efficiency without compromising its accuracy. The model was tested for MISO and MIMO wireless transmitters. The simulations and measurement results revealed that the proposed model gives excellent accuracy when modeling MIMO transmitters with different branch coupling factors.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.821
Threshold uncertainty score0.681

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 head0.027
GPT teacher head0.239
Teacher spread0.212 · 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