MétaCan
Menu
Back to cohort
Record W2380763832

An Improved SLM for PAPR Reduction of OFDM

2010· article· en· W2380763832 on OpenAlexvenueno aff
Jun You

Bibliographic record

VenueMicrocomputer applications · 2010
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsnot available
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingComputer scienceTransmitterBit error rateReduction (mathematics)Bandwidth (computing)MultiplexingAlgorithmElectronic engineeringSIGNAL (programming language)Real-time computingTelecommunicationsChannel (broadcasting)Mathematics
DOInot available

Abstract

fetched live from OpenAlex

To address the problem that the peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing (OFDM) systems is too high, an improved selected mapping (SLM) is proposed. By scaling the selected signal’s amplitude and packeting the OFDM symbols in the transmitter, the improved SLM saves the system’s bandwidth and reduce the PAPR efficiently with no side information to be sent. At the same time, the random phase sequence information is rapidly recovered by using related detection algorithm, which largely raises the detective efficiency in the receiver. The simulation results show that the improved SLM could reduce the PAPR more efficiently while the bit error rate (BER) is similar to the one of the typical SLM.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.458
Threshold uncertainty score0.463

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 head0.005
GPT teacher head0.237
Teacher spread0.232 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueMicrocomputer applicationsSame topicPAPR reduction in OFDMFrench-language works237,207