MétaCan
Menu
Back to cohort
Record W2689389728 · doi:10.1109/ccece.2017.7946743

PAPR and BER performance analysis of OFDM system with multi-h CPFSK mapper

2017· article· en· W2689389728 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 institutionsWestern University
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingBit error rateNakagami distributionPhase-shift keyingFadingComputer scienceFrequency-shift keyingReduction (mathematics)Rayleigh fadingElectronic engineeringAlgorithmMathematicsTelecommunicationsEngineeringDemodulationChannel (broadcasting)

Abstract

fetched live from OpenAlex

Multi-h CPFSK mapper in an OFDM system can offer significant gain in both PAPR and bit error rate probability. The OFDM PAPR problem is addressed and investigated using SLM reduction technique. Next, an OFDM system with a multi-h CPFSK mapper is considered and its performance is evaluated in terms of the upper and lower bounds on bit error rate probability, and a closed form expression is obtained. Also, the system performance is examined over Rayleigh and Nakagami-m fading channels. The simulation and analytical results show that the performance of the system is superior than the OFDM system with BPSK and single-h CPFSK mappers.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score0.265

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 communication0.0000.000
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 head0.011
GPT teacher head0.210
Teacher spread0.199 · 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
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicPAPR reduction in OFDMFrench-language works237,207