MétaCan
Menu
Back to cohort
Record W2154465178 · doi:10.1109/icc.2008.264

MIMO Optical Wireless Channels Using Halftoning

2008· article· en· W2154465178 on OpenAlexaff
Mahmoud Mohamed, Awad Dabbo, Steve Hranilovic

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMIMOOptical wirelessComputer scienceSpatial multiplexingTransmitterChannel (broadcasting)PixelFrame (networking)HolographyWirelessElectronic engineeringBinary numberChannel capacitySpatial correlationOptical performance monitoringTelecommunicationsOpticsEngineeringPhysicsComputer visionMathematics

Abstract

fetched live from OpenAlex

Two-dimensional (2D) optical intensity channels exist in a variety of applications including holographic storage, page-oriented memories, optical interconnects, 2D barcodes, as well as MIMO wireless optical links. This paper considers the capacity of such channels when the transmitted signal is binary-level. Strict spatial alignment between transmitter and receiver is not required nor is independence among the spatial channels. Spatial discrete multitone modulation is combined with digital image halftoning to produce a binary-level transmit image. Unlike earlier work, this paper considers imagers with pixels of fixed size and quantifies the tradeoff between frame rate, array size and capacity per frame. An experimental prototype pixelated wireless optical channel is constructed, and the channel parameters are measured. With a measured channel model, rates on the order of 450 Mbps are predicted for aim link using 0.5 megapixel arrays at a frame rate of 7 kfps.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.242
Teacher spread0.201 · 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

Citations9
Published2008
Admission routes1
Has abstractyes

Explore more

Same topicOptical Wireless Communication TechnologiesFrench-language works237,207