MétaCan
Menu
Back to cohort
Record W4398787798 · doi:10.1109/lmwt.2024.3400618

Low Complexity Digital Predistortion for Multiband Radio Over Fiber Systems

2024· article· en· W4398787798 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 Microwave and Wireless Technology Letters · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsConcordia University
FundersNational Natural Science Foundation of China
KeywordsPredistortionComputer scienceTelecommunicationsElectronic engineeringEngineeringAmplifierBandwidth (computing)

Abstract

fetched live from OpenAlex

Nonlinear distortion is one of the limiting factors in radio over fiber (RoF) transmission systems. To suppress the nonlinear distortion, digital predistortion (DPD) has been investigated considerably. However, DPD for multiband signals becomes very complex. In this work, a new low-complexity multiband DPD is proposed, in which in-band and out-of-band distortions are separated and the out-of-band distortion is evaluated by sum and differences of all input signals instead of all individual input signals; thus, complexity is reduced. A five-band 20-MHz 64-quadrature amplitude modulation (QAM) orthogonal frequency division multiplexing (OFDM) signals over an 8-km RoF link with the DPD is tested. The average improvement of error vector magnitude (EVM) is 8.1 dB. The model is further validated by simulation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.770

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 head0.012
GPT teacher head0.228
Teacher spread0.216 · 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