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Record W2154465178 · doi:10.1109/icc.2008.264

MIMO Optical Wireless Channels Using Halftoning

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

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

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.

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 score0.572
Threshold uncertainty score0.509

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 science0.0000.000
Research integrity0.0000.000
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 head0.042
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