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Record W2128270958 · doi:10.1109/cjece.2004.1425795

Linear-complexity detection with iterative processing for space-time coded systems

2004· article· en· W2128270958 on OpenAlexaffvenue
Naveen Mysore, Jan Bajcsy

Bibliographic record

VenueCanadian Journal of Electrical and Computer Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsMcGill University
Fundersnot available
KeywordsMIMOComputer scienceSpace–time codeDecoding methodsChannel state informationAlgorithmFadingDemodulationTransmission (telecommunications)Channel (broadcasting)Rayleigh fadingTelecommunications linkTurboContext (archaeology)TransmitterTurbo codeErgodic theoryElectronic engineeringWirelessTelecommunicationsMathematicsEngineering

Abstract

fetched live from OpenAlex

This paper considers wireless data transmission over multi-input, multi-output (MIMO) channels when only the receiver has perfect channel state information. A linear-complexity space-time detector is derived in the context of a turbo-code-based space-time transmitter and iterative processing (turbo detection, demodulation and decoding). Simulation results illustrate that the proposed receivers, suitable for uplink transmission, perform at a level within 2 to 3 dB of the ergodic channel capacity on MIMO channels affected by uncorrelated and correlated Rayleigh flat fading.

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: Methods · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score0.446

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 head0.009
GPT teacher head0.196
Teacher spread0.187 · 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
GenreMethods

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

Citations5
Published2004
Admission routes2
Has abstractyes

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