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Record W4407128653 · doi:10.1109/lwc.2025.3538822

Parameter-Based Estimation of Block Time-Varying Channels in OTFS Modulation Systems

2025· article· en· W4407128653 on OpenAlexaff
Mohammed K. AbuFoul, Deeb Assad Tubail, Mohammed Zourob, Salama Ikki

Bibliographic record

VenueIEEE Wireless Communications Letters · 2025
Typearticle
Languageen
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsTellabs (Canada)Lakehead University
Fundersnot available
KeywordsBlock (permutation group theory)Modulation (music)Computer scienceEstimation theoryTime–frequency analysisControl theory (sociology)AlgorithmElectronic engineeringMathematicsTelecommunicationsRadarPhysicsArtificial intelligenceEngineeringAcoustics

Abstract

fetched live from OpenAlex

This letter aims to estimate a Block Time-Varying channel by identifying its key parameters using a limited number of pilots occupying a subset of transmitted symbols. The method is evaluated in the context of an Orthogonal Time-Frequency Space (OTFS) system, proposing two estimators for different levels of available information. The first, based on received signals, employs Maximum Likelihood (ML) with a four-dimensional grid search, simplified to two dimensions via a linear model reformulation. The second estimator incorporates prior knowledge of parameter transitions using the Extended Kalman Filter (EKF). Performance is evaluated against theoretical lower bounds.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.706

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 science0.0010.000
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 head0.019
GPT teacher head0.259
Teacher spread0.239 · 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 designSimulation or modeling
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

Citations4
Published2025
Admission routes1
Has abstractyes

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