MétaCan
Menu
Back to cohort
Record W2093423039 · doi:10.1109/glocomw.2013.6825129

BER of subcarrier MPSK/MDPSK modulated OWC systems in Gamma-Gamma turbulence

2013· article· en· W2093423039 on OpenAlexaff
Xuegui Song, Julian Cheng, Mohamed‐Slim Alouini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsBit error rateSubcarrierPhase-shift keyingMathematicsTurbulenceWirelessAlgorithmPhysicsControl theory (sociology)Applied mathematicsComputer scienceTelecommunicationsChannel (broadcasting)Orthogonal frequency-division multiplexingDecoding methodsArtificial intelligence

Abstract

fetched live from OpenAlex

Bit-error rate (BER) performance of subcarrier M-ary phase-shift keying (MPSK) and M-ary differential PSK (MDPSK) is analyzed for optical wireless communications in Gamma-Gamma turbulence. We study the relation between the exact BER and the approximate BER, which is obtained by dividing the symbol error rate by the number of bits per symbol, for subcarrier MPSK and MDPSK modulations. The asymptotic performance gap between the exact and the approximate BERs is quantified analytically through our asymptotic analyses. The accuracy of the approximate BER of both MPSK and MDPSK depends on the channel conditions. Under weak turbulence conditions, the approximate BER expression can be used to predict the system performance with high accuracy, while under strong turbulence conditions the approximate BER becomes inaccurate and can only serve as a loose lower bound of the exact BER. The asymptotic BER performance loss of MDPSK with respect to MPSK is also quantified analytically.

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 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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.480

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 head0.007
GPT teacher head0.181
Teacher spread0.174 · 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 teacher head, 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

Citations2
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicOptical Wireless Communication TechnologiesFrench-language works237,207