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Record W2974327400 · doi:10.1109/cjece.2019.2920896

A Sufficient Condition for General QAM Complementary Sequence Pairs

2020· article· en· W2974327400 on OpenAlexvenueno aff
Fanxin Zeng, Yue Zeng, Lisheng Zhang, Xiping He, Guixin Xuan, Zhenyu Zhang

Bibliographic record

VenueCanadian Journal of Electrical and Computer Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsBinary Golay codeComplementary sequencesQAMBinary numberAlgorithmMathematicsSequence (biology)Quadrature amplitude modulationInteger (computer science)Pseudorandom binary sequenceMultiplexingTernary operationComputer scienceTelecommunicationsDiscrete mathematicsArithmeticBit error rateDecoding methods

Abstract

fetched live from OpenAlex

This paper investigates the construction of QAM Golay complementary sequence pairs (CSPs) based on standard binary Golay-Davis-Jedwab (GDJ) CSPs. In order to guarantee that the proposed construction produces QAM Golay CSPs, a sufficient condition that the coefficients of offsets should satisfy is developed, which is fit for finding all the coefficients by a computer. In particular, all the coefficients of offsets over the 64- and 256-QAM constellations are given. The proposed construction includes Zeng's and Ma et al.'s ones as special cases. The inputs of resultant sequence pairs are binary signals rather than quaternary ones, which means that the resulting sequences are fit for such QAM systems that merely depend on binary inputs. The obtained QAM Golay CSPs can be applied to orthogonal frequency division multiplexing systems so as to reduce peak envelope power of their signals.

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)0.013
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.018
GPT teacher head0.204
Teacher spread0.186 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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