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Record W2133295573 · doi:10.1109/twc.2004.833525

Analysis and Design Criteria for Trellis-Coded Modulation With Differential Space-Time Transmit Diversity

2004· article· en· W2133295573 on OpenAlexaff
Poramate Tarasak, V.K. Bhargava

Bibliographic record

VenueIEEE Transactions on Wireless Communications · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
Fundersnot available
KeywordsTrellis modulationBlock codeAlgorithmSpace–time block codeAdditive white Gaussian noiseFadingComputer scienceMathematicsConcatenated error correction codeTelecommunicationsRayleigh fadingTrellis (graph)Convolutional codeDecoding methodsWhite noise

Abstract

fetched live from OpenAlex

In this letter, concatenation of trellis-coded modulation (TCM) with differential space-time block codes (DSTBC) is considered under frequency-flat Rayleigh-fading channels with and without perfect interleaver. It is shown that the design criteria of TCM concatenated with DSTBC are exactly the same as that of TCM concatenated with space-time block codes (STBC) in perfectly known channels. They are effective code length over span two symbol intervals and minimum product-sum distance over span two symbol intervals. Based on the design criteria, several new rate-2/3 systematic Ungerboeck's TCM schemes have been found by computer search. They outperform existing optimal TCM schemes designed for additive white Gaussian noise or flat fading channels.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.261
Teacher spread0.233 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations9
Published2004
Admission routes1
Has abstractyes

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