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Record W2042750652 · doi:10.1109/tmtt.2012.2201742

Novel Modeling and Calibration Approach for Multiport Receivers Mitigating System Imperfections and Hardware Impairments

2012· article· en· W2042750652 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 · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Amplifier Design
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsWidebandElectronic engineeringComputer scienceLinearizationBandwidth (computing)WirelessDetectorCode division multiple accessEngineeringTelecommunicationsNonlinear system

Abstract

fetched live from OpenAlex

Factors limiting and degrading the performance of a multiport-based receiver system for wideband signals are modeled and a suitable calibration approach is proposed in this paper. The proposed calibration approach uses a new model for linearization of diode power detectors suitable for wideband real (modulated) wireless signals. To verify the proposed model and calibration procedure, a 2-18-GHz wideband six-port-based receiver system is set up and its performance is verified using wireless signals having different bandwidth and modulation schemes. The new calibration algorithm improved the error vector magnitude (EVM) of the receiver system from 7.9% to 1.6% for a 64-QAM signal with a bandwidth of 2 MHz and a data rate of 12 Mb/s. To show the usefulness of the model for real communication signals, wideband code division multiple access (WCDMA) and wireless local area network (WLAN) signals are received and EVM of 4.7% and 3.4% are reported for the WCDMA and the WLAN signals, respectively.

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: Methods · Consensus signal: none
Teacher disagreement score0.794
Threshold uncertainty score0.765

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 head0.234
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