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Record W1617750981 · doi:10.1109/iwcmc.2015.7289308

Compressed sensing-based time-varying channel estimation in UWA-OFDM networks

2015· article· en· W1617750981 on OpenAlexaff
Yi Zhang, R. Venkatesan, Cheng Li, Octavia A. Dobre

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUnderwater Vehicles and Communication Systems
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingCompressed sensingChannel (broadcasting)Computer scienceUnderwater acoustic communicationInterference (communication)SIGNAL (programming language)MultiplexingElectronic engineeringTelecommunicationsAlgorithmUnderwaterEngineeringGeography

Abstract

fetched live from OpenAlex

Underwater acoustic (UWA) channels are often characterized as time-varying systems which result in intercarrier interference (ICI) in the reception of orthogonal frequency division multiplexing (OFDM) signals. Recently, compressed sensing (CS) has gained a fast-growing interest by exploiting the sparse nature of UWA channels in OFDM communication networks. This paper studies selected characterizations of the UWA channels, and reviews several mathematical UWA channel models in the literature. Moreover, we present a CS-based sparse channel estimation based on a recently-established statistical channel model, which incorporates acoustic signal propagation laws and random local displacements. The sparse coefficients can be estimated using CS-based reconstruction algorithms.

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: none
Teacher disagreement score0.965
Threshold uncertainty score0.416

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 head0.028
GPT teacher head0.225
Teacher spread0.197 · 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
Published2015
Admission routes1
Has abstractyes

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