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Record W2160220809 · doi:10.1109/26.886468

Further analytical results on the joint detection of cochannel signals using diversity arrays

2000· article· en· W2160220809 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 · 2000
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsFadingComputer scienceJoint (building)Antenna diversityElectronic engineeringAntenna (radio)Diversity combiningAlgorithmBinary numberChannel (broadcasting)Cooperative diversityKeyingPhase-shift keyingBase stationTelecommunicationsMathematicsBit error rateEngineeringArithmetic

Abstract

fetched live from OpenAlex

We derive a fully analytical expression for the union bound on symbol-error rate for the joint detection of several cochannel fading signals using a diversity antenna array, putting numerical results previously published on a firm analytical base. We prove that with pilot-based multiuser channel estimation, any number of users can enjoy diversity order equal to the number of antennas, and we quantify the performance penalty relative to single-user binary phase-shift keying as a function of number of users, constellation density, and number of antennas. We also demonstrate the interdependence of all users participating in the detection process.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.971
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
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0030.000
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 head0.137
GPT teacher head0.314
Teacher spread0.177 · 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