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Record W2099847574 · doi:10.1109/icassp.2004.1326864

Information lossless full rate full diversity cyclotomic linear dispersion codes

2004· article· en· W2099847574 on OpenAlexaff
Jiankang Zhang, K.M. Wong, Timothy N. Davidson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBlock codeLinear codeSpace–time block codeOrthonormal basisComputer scienceCode rateCode (set theory)AlgorithmMathematicsTheoretical computer scienceTelecommunicationsDecoding methods

Abstract

fetched live from OpenAlex

It has recently been determined (by others) that one can construct full rate full diversity linear space-time block codes without a reduction in the achievable information rate. In this paper, we address two issues in those designs. One issue is whether the rotation matrix and the Diophantine number can be systematically and efficiently constructed for an arbitrary number of transmitter antennas and receiver antennas and whether the signal constellation is necessarily limited to PAM or QAM. The other issue is whether the currently available square designs can be generalized to a rectangular design and in particular, to a linear dispersion code design. This paper resolves these issues by proposing a trace-orthonormal linear space-time block code and linear dispersion code, and giving a systematic method to design such a code family. By carefully selecting V-structured matrices or conjugate V-structured matrices in this family, we can systematically and efficiently design information lossless full rate full diversity cyclotomic space-time codes.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.585
Threshold uncertainty score0.494

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 communication0.0000.001
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 head0.222
Teacher spread0.213 · 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
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

Citations10
Published2004
Admission routes1
Has abstractyes

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