MétaCan
Menu
Back to cohort
Record W2170260879 · doi:10.1109/tcomm.2009.04.070118

Fast multiple-symbol detection for free-space optical communications

2009· article· en· W2170260879 on OpenAlex

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

VenueIEEE Transactions on Communications · 2009
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceKeyingSymbol (formal)Metric (unit)Channel (broadcasting)Detection theoryAlgorithmBit error rateChannel state informationUpper and lower boundsModulation (music)Phase-shift keyingElectronic engineeringMathematicsTelecommunicationsDetectorEngineering

Abstract

fetched live from OpenAlex

In this paper, we investigate noncoherent detection, i.e. detection assuming the absence of channel state information at the receiver, of on-off keying in an intensity modulation and direct detection (IM/DD) free-space optical (FSO) system. To partially recover the performance loss associated with symbol- by-symbol noncoherent detection, we consider the application of multiple-symbol detection (MSD), in which block-wise decisions are made using an observation window of several bit intervals. Specifically, we develop a fast search algorithm for optimal MSD and propose a reduced-complexity decision metric suitable for suboptimal MSD; performance results confirm that the optimal and suboptimal metrics perform comparably well. Significantly, the complexity of our receiver, on a per bit-decision basis, is only logarithmically dependent on the observation window size. We also present the framework for a decision-feedback receiver and obtain performance expressions for the ideal case of error-free feedback; these expressions serve as an upper bound to the performance of MSD. Analytical and simulation results indicate that as the observation window size increases, the performance of the MSD receiver approaches that of detection with channel state information. The conclusion is reached that the proposed implementation provides an attractive low-complexity mechanism for performing noncoherent MSD in FSO systems.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.891
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0040.000
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 head0.031
GPT teacher head0.267
Teacher spread0.235 · 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