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A Photonic Transceiver for the Aggregation and Disaggregation of Microwave Signals Based on an Optical Frequency Comb Source

2023· article· en· W4390481020 on OpenAlexaff
Haikun Huang, Shengkang Zeng, Lingzhi Li, Jiejun Zhang, Jianping Yao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsUniversity of Ottawa
FundersNational Natural Science Foundation of China
KeywordsPhase-shift keyingBit error rateKeyingOptical Carrier transmission ratesPhotonicsPhysicsQuadrature amplitude modulationTransceiverModulation (music)MicrowaveBasebandElectronic engineeringComputer scienceTelecommunicationsOpticsBandwidth (computing)Transmission (telecommunications)EngineeringRadio over fiberDecoding methodsWireless

Abstract

fetched live from OpenAlex

A photonic transceiver for the aggregation and disaggregation of microwave signals based on an optical frequency comb source is proposed and experimentally demonstrated. The key device is a dual-polarization dual-drive Mach-Zehnder modulator (DP-DDMZM) which is employed to perform signal aggregation and disaggregation. In the aggregation mode, four binary phase shift keying (BPSK) microwave signals with each having a bit rate of 2 Gbps at different frequencies received by four antennas are aggregated into two quadrature phase shift keying (QPSK) single-sideband (SSB) modulation optical signals with orthogonal polarizations. The spectral efficiency is quadrupled with a combined bit rate of 8 Gbps. After coherent detection, the aggregated signals are decoded. The error vector amplitude (EVM) is 19.93% and the bit error rate (BER) is 2.61 X 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−7</sup>. In the disaggregation mode, a QPSK microwave signal with a bit rate of 4 Gbps received by an antenna is disaggregated into two BPSK optical signals, with each disaggregated signal having a bit rate of 2 Gbps and an EVM of 13.75%.

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.

How this classification was reachedexpand

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.281

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 head0.015
GPT teacher head0.230
Teacher spread0.215 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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