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Record W2164764855 · doi:10.1109/lcomm.2004.835303

On the Code and Interleaver Design of Broadband OFDM Systems

2004· article· en· W2164764855 on OpenAlexaff
X.-F. Wang, Yousef R. Shayan, Ming Zeng

Bibliographic record

VenueIEEE Communications Letters · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsInterleavingBlock codeOrthogonal frequency-division multiplexingHamming codeHamming distanceTrellis modulationComputer scienceHamming boundCoding gainAlgorithmConcatenated error correction codeForward error correctionCoding (social sciences)Space–time block codeCode division multiple accessLinear codeTelecommunicationsMathematicsDecoding methodsFadingChannel (broadcasting)Statistics

Abstract

fetched live from OpenAlex

In this letter, we study the performance of space-frequency-coded orthogonal frequency-division modulation systems over multiple-input multiple-output frequency-selective channels. The diversity and coding advantages are derived in terms of the minimum Hamming distance and the minimum squared product distance of the code as well as the relative frequency locations (tones) where a pair of codewords with the minimum Hamming distance differ. These relationships between performance and well-defined code parameters provide new insight to code construction and interleaving design. In addition, we propose a block interleaver that yields nearly optimal coding advantage for space-frequency trellis 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 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)0.001
metaresearch head score (Gemma)0.003
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.256
Teacher spread0.219 · 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

Citations19
Published2004
Admission routes1
Has abstractyes

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