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Record W2115358448 · doi:10.1109/glocom.2005.1578472

An analytical solution for the BER of an individually optimal single cochannel interferer BPSK receiver

2005· article· en· W2115358448 on OpenAlex
Amir Masoud Rabiei, Norman C. Beaulieu

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

VenueGLOBECOM '05. IEEE Global Telecommunications Conference, 2005. · 2005
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhase-shift keyingAdditive white Gaussian noiseBit error rateInterference (communication)KeyingAlgorithmComputer scienceBinary numberWhite noiseNoise (video)Electronic engineeringMathematicsTelecommunicationsDecoding methodsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

The exact bit error rate (BER) of a synchronous individually optimal receiver (IOR) used to detect a binary phase-shift keying (BPSK) signal distorted by a like-modulated signal and additive white Gaussian noise (AWGN) is derived. It is shown that the BER expression decomposes into the probability of error of BPSK in AWGN plus an interference term. It is observed that as the noise decreases the IOR performance approaches the performance of a single cochannel interferer jointly optimal receiver.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.751
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.000
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 head0.044
GPT teacher head0.314
Teacher spread0.270 · 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