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Record W2160518835 · doi:10.1109/glocom.2003.1258531

Performance Analysis of a Jointly Optimal BPSK Receiver in Cochannel Interference

2005· article· en· W2160518835 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicBlind Source Separation Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhase-shift keyingInterference (communication)Additive white Gaussian noiseComputer scienceSIGNAL (programming language)Signal-to-noise ratio (imaging)AlgorithmBinary numberBit error ratePhase (matter)KeyingSingle antenna interference cancellationControl theory (sociology)Electronic engineeringWhite noiseMathematicsTelecommunicationsPhysicsDecoding methodsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

A jointly optimal detection scheme for a binary phase shift keying signal in the presence of a cochannel interferer and additive white Gaussian noise has been recently reported. The average error rate performance of this detection scheme was determined by extensive simulation. This paper develops an analytical solution for the average error rate performance of this jointly optimal detection scheme. An interesting characteristic of the solution is that it takes different analytical forms depending on the region of signal-to-interference ratio. These regions depend, in turn, on the phase difference between the desired signal and the interference signal. The analytical solution is exact and has excellent agreement with simulation results. These results show that this jointly optimal detection scheme can have good performance at both small and large values of signal-to-interference ratio.

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: none
Teacher disagreement score0.671
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.019
GPT teacher head0.264
Teacher spread0.246 · 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

Quick stats

Citations8
Published2005
Admission routes1
Has abstractyes

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