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Record W4412985054 · doi:10.1109/jlt.2025.3596057

A Novel CMOS SPAD Receiver for Optical Wireless Communication

2025· article· en· W4412985054 on OpenAlexafffund
Junzhi Liu, Wei Jiang, Yeganeh Nasrollahzadeh, Shiva Kumar, M. Jamal Deen

Bibliographic record

VenueJournal of Lightwave Technology · 2025
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCMC Microsystems
KeywordsCMOSWirelessOptical communicationElectronic engineeringOptical wirelessComputer scienceElectrical engineeringTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Single-photon avalanche Diodes (SPADs) are widely considered to have promising prospects in the field of optical wireless communication (OWC). In this paper, a novel SPAD-based optical sensor was designed, fabricated, and tested for the application of an OWC receiver. In the application of SPAD-based OWC, intersymbol interference (ISI) effects can be a challenge to improve the performance of SPAD receivers. Therefore, this SPAD sensor was integrated with two unique timing control modes: the clock-driven (CD) mode and the time-gated (TG) mode to reduce the ISI effect in different communication conditions. The bit error rate (BER) testing results showed that our 4 × 4 SPAD receivers exhibited high sensitivity, achieving a BER of 3.8 × 10-3at a signal power of -71 dBm and a background optical power of -84 dBm. Additionally, by comparing test results with simulation results, we can observe a high degree of congruence between experimental outcomes and simulated results.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.248
Teacher spread0.239 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2025
Admission routes2
Has abstractyes

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