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Record W2972037027 · doi:10.1109/mwsym.2019.8700932

Single-Input Single-Output Digital Predistortion of Multi-user RF Beamforming Arrays

2019· article· en· W2972037027 on OpenAlex
Eric Ng, Ahmed Ben Ayed, Patrick Mitran, Slim Boumaiza

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
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPredistortionBeamformingComputer scienceRadio frequencyElectronic engineeringTelecommunicationsEngineeringAmplifierBandwidth (computing)

Abstract

fetched live from OpenAlex

We investigate the application of single-input single-output (SISO) digital predistortion (DPD) to mitigate the nonlinearity in millimeter-wave multi-user RF beamforming arrays. In principle, SISO DPD may not be sufficient to linearize such arrays as a multiple-input one may be required due to coupling between the sub-array antennas. Nevertheless, in practice, the coupling between antennas of different sub-arrays may be much smaller than the coupling between antennas of the same sub-array. It is first shown mathematically that if the coupling between sub-arrays is small, then SISO DPD is sufficient to linearize such arrays. This is then confirmed in practice by linearizing two co-located 64-element sub-arrays driven by 800 MHz modulated signals at 28 GHz. Using four sets of SISO DPD coefficients, the EVM and ACPR were improved from as much as 8% and 30 dBc to better than 2% and 40 dBc, respectively, across all steering angle combinations of the two sub-arrays.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score1.000

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 head0.020
GPT teacher head0.201
Teacher spread0.181 · 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

Quick stats

Citations14
Published2019
Admission routes1
Has abstractyes

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