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Record W2036524501 · doi:10.1155/wcn.2005.20

Adaptive Denoising and Equalization of Infrared Wireless CDMA System

2005· article· en· W2036524501 on OpenAlex
Xavier Fernando, Balakanthan Balendran

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

VenueEURASIP Journal on Wireless Communications and Networking · 2005
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsComputer scienceMultipath propagationProcess gainBandwidth (computing)CDMA spectral efficiencyElectronic engineeringFilter (signal processing)WirelessTelecommunicationsCode division multiple accessEqualization (audio)Interference (communication)Raised-cosine filterNoise (video)Adaptive filterReal-time computingSpread spectrumRoot-raised-cosine filterChannel (broadcasting)Low-pass filterAlgorithmArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

Infrared has abundant, unregulated bandwidth enabling rapid deployment at low cost. However, safety limits on power emission levels (IEC825), large noise due to ambient lighting, and multipath dispersion remain as hurdles in diffused indoor environments. Especially, the high-frequency periodic interference produced by fluorescent lights is a major concern. Spread spectrum techniques enable low-power operation and noise rejection, at the expense of large processing gain. In this paper, we quantify the noise received and propose an adaptive FIR filter to jointly cancel the multipath dispersion and the fluorescent light noise in an infrared CDMA system. From analytical and simulation results, the adaptive filter significantly enhances the noise rejection capability of the CDMA system and tracks well the quasistationary indoor wireless channel. Our results show tenfold improvement in the BER for a given SNR and processing gain due to the adaptive filter. The filter also performs well in the multiuser environment.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.980
Threshold uncertainty score0.848

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 science0.0010.000
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 head0.030
GPT teacher head0.251
Teacher spread0.221 · 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