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Record W2155199613 · doi:10.1109/tcomm.2004.826415

Subspace-Based Active User Identification for a Collision-Free Slotted Ad Hoc Network

2004· article· en· W2155199613 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 · 2004
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceTransmitterWireless ad hoc networkIdentifierSubspace topologyComputer networkFalse alarmBandwidth (computing)Interference (communication)Node (physics)AlgorithmWirelessChannel (broadcasting)TelecommunicationsEngineering

Abstract

fetched live from OpenAlex

We propose a novel spreading code scheme, transmitter-receiver-based code, for wireless ad hoc networks. The design facilitates collision resolution using multiuser detection at each node, and is more bandwidth efficient than creating orthogonal channels in time or frequency. A subspace-based receiver structure is introduced, which identifies users of interest, or "active" users, with minimal prior information on the spreading code ensemble. A subspace-based blind multiuser detector can then be implemented to suppress multiaccess interference. The performance of the proposed active user identifier is studied by investigating its false alarm rate P/sub f/ and miss rate P/sub m/. Tradeoffs between P/sub f/ and P/sub m/ are discussed, and a graphical method to determine the threshold value d/sub th/ of the decision statistic used in discriminating between active and inactive channels is introduced.

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), Science and technology studies, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.770
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
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0080.000
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 head0.046
GPT teacher head0.313
Teacher spread0.267 · 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