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Record W1985394441 · doi:10.1109/lpt.2012.2188502

Low-Complexity Optical Distribution of Gb/s BPSK UWB Signals

2012· article· en· W1985394441 on OpenAlexaff
Mehrdad Mirshafiei, Leslie A. Rusch

Bibliographic record

VenueIEEE Photonics Technology Letters · 2012
Typearticle
Languageen
FieldEngineering
TopicUltra-Wideband Communications Technology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsIntersymbol interferencePhase-shift keyingComputer scienceOscilloscopeBit error rateElectronic engineeringMultipath propagationSIGNAL (programming language)Optical wirelessUltra-widebandPulse-amplitude modulationPhysicsWirelessTelecommunicationsDecoding methodsPulse (music)EngineeringDetectorChannel (broadcasting)

Abstract

fetched live from OpenAlex

Optical transport of ultra-wideband (UWB) signals extends the reach of these power-limited signals to several kilometers. We propose and experimentally demonstrate a simple and low-cost optical method to generate UWB pulses. We use few optical components (source/modulator/photodetector), in contrast to most other optical generation techniques. UWB pulses complying with the U.S. Federal Communications Commission spectral mask are generated by modulating the intensity of a continuous-wave laser with a combined signal consisting of the data signal and a sinusoidal signal. For impulse radio UWB, binary phase-shift-keying is accomplished simply by adjusting the amplitudes of the data and the sinusoidal signal. Wireless propagation of the UWB impulses is investigated experimentally at a very high bit rate. The receiver is implemented using a real-time oscilloscope to capture the received waveforms followed by offline signal processing. In particular, we consider a minimum-mean-square error equalizer to counter the multipath-induced intersymbol interference encountered at 1.75 Gb/s. Equalization brings the bit-error-rate within the forward-error correction limit of after 2.5 m of wireless propagation at 1.75 Gb/s.

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 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 score0.033
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
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.229
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.

Study designBench or experimental
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
Published2012
Admission routes1
Has abstractyes

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