MétaCan
Menu
Back to cohort
Record W2110064243 · doi:10.1109/cwit.2011.5872119

Peak power analysis of MC-CDMA employing Golay complementary sequences

2011· article· en· W2110064243 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsLakehead University
Fundersnot available
KeywordsBinary Golay codeCode division multiple accessComplementary sequencesCoding (social sciences)Telecommunications linkAlgorithmComputer scienceSequence (biology)Power (physics)MathematicsElectronic engineeringTelecommunicationsStatisticsEngineeringPhysics

Abstract

fetched live from OpenAlex

Golay complementary sequences are a good solution to reduce the high peak-to-average power ratio (PAPR) of multicarrier communication systems. In this paper, we present a simple but novel technique to develop theoretical PAPR bounds of downlink MC-CDMA system using Golay complementary sequences for spreading and coding. The developed PAPR bounds are independent of the spreading factor in uncoded MC-CDMA. Furthermore, they have no dependency on the number of spreading processes as well as the spreading factor in coded MC-CDMA. Simulation results demonstrate that the theoretical bounds are well followed by 99.9% PAPRs which are also independent of spreading factors (for uncoded and coded cases), and the number of spreading processes (for coded case only). Practically, the independency gives us a useful insight for peak power control in MC-CDMA employing Golay complementary sequences.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.046
GPT teacher head0.253
Teacher spread0.207 · 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

Quick stats

Citations2
Published2011
Admission routes1
Has abstractyes

Explore more

Same topicPAPR reduction in OFDMFrench-language works237,207