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Record W1997006052 · doi:10.1049/ip-com:20040365

Performance analysis of multicarrier CDMA systems with parallel and serial concatenated coding in fading channels

2004· article· en· W1997006052 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

VenueIEE Proceedings - Communications · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer scienceTurbo codeFadingBit error rateAlgorithmConvolutional codeCode division multiple accessConcatenated error correction codeRayleigh fadingMultipath propagationTurbo equalizerSerial concatenated convolutional codesElectronic engineeringTelecommunications linkDecoding methodsTelecommunicationsChannel (broadcasting)Block codeEngineering

Abstract

fetched live from OpenAlex

The authors present a bit error rate performance analysis of multicarrier code division multiple access (MC-CDMA) systems with turbo and serial concatenated convolutional coding (SCCC) in multipath fading channels. The performance analysis is done for maximal ratio combining and minimum mean square error combining detection in the downlink system. Upper bounds to the average bit error probability are presented for a punctured turbo code and for an SCCC code of similar decoding complexity. These analytical bounds are derived for fully interleaved Rayleigh fading channels. The bit error rate performance is also verified by simulations in the regions of low signal-to-noise ratios. The analytical and simulation results illustrate the relative merits of the turbo and SCCC codes for MC-CDMA systems and their suitability to achieve very low error rates in wireless data applications.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.251
Teacher spread0.230 · 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