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Record W1970894474 · doi:10.1109/50.983229

Multirate optical fast frequency hopping CDMA system using power control

2002· article· en· W1970894474 on OpenAlexaff
Elie Inaty, Hossam M. H. Shalaby, Paul Fortier, Leslie A. Rusch

Bibliographic record

VenueJournal of Lightwave Technology · 2002
Typearticle
Languageen
FieldEngineering
Topicgraph theory and CDMA systems
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCode division multiple accessComputer sciencePower controlElectronic engineeringFrequency-hopping spread spectrumTransmission (telecommunications)Quality of serviceInterference (communication)Computer networkSpread spectrumBit error ratePower (physics)Real-time computingTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

This paper addresses the problem of real-time multimedia transmission in fiber-optic networks using code division multiple access (CDMA). We present a multirate optical fast frequency hopping CDMA (OFFH-CDMA) system architecture using fiber Bragg gratings (FBGs). In addition, we argue that, in multimedia applications, different services have different quality of service (QoS) requirements; hence, the user only needs to use the minimum required power to transmit the signal, such that the required signal-to-interference ratio (SIR) is met. We show that a variable bit rate optical communication system with variable QoS can be implemented by way of power control with great efficiency. Present-day multirate optical CDMA systems concentrate on finding the code structure that supports a variable rate system, neglecting the importance of the transmission power of active users on the multiple access interference (MAI) and, therefore, on the system capacity. We assign different power levels to each rate through a power control algorithm using variable optical attenuators, which minimizes the interference and, at the same time, provides variable QoS constraints for different traffic types. Although we are using a code family that preserves good correlation properties between codes of different lengths, simulations show a great improvement in the system capacity when power control is used.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.188
Teacher spread0.179 · 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 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

Citations105
Published2002
Admission routes1
Has abstractyes

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