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Record W1966805475 · doi:10.1109/pimrc.2011.6139731

Multicarrier HF communications with amplify-and-forward relaying

2011· article· en· W1966805475 on OpenAlexaff
Mohammad Reza Heidarpour, Murat Uysal

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingComputer scienceElectronic engineeringTransmission (telecommunications)WirelessCommunications systemKey (lock)FadingPairwise error probabilityComputer networkTelecommunicationsEngineeringChannel (broadcasting)

Abstract

fetched live from OpenAlex

High-frequency (HF) radio communication has been recognized as the primary means for long-range wireless communications since the advent of radio. With its unique features, HF communication continues to be used for a wide range of civilian, government and military applications as a powerful alternative to a myriad of more sophisticated communication systems. However demanding requirements of high-speed data communications impose new requirements on the HF system design and innovative approaches are required. In this paper, building upon the promising concept of cooperative transmission, we investigate the performance of a multicarrier coded HF system with amplify-and-forward relaying. Specifically, we consider orthogonal frequency division multiplexing (OFDM) with bit-interleaved coded modulation (BICM) and demonstrate the achievable diversity through the derivation of pairwise error probability. We also conduct Monte Carlo simulations to confirm the analytical derivations and present performance comparisons.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.891
Threshold uncertainty score0.268

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 science0.0010.001
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 head0.098
GPT teacher head0.280
Teacher spread0.182 · 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 designTheoretical or conceptual
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

Citations6
Published2011
Admission routes1
Has abstractyes

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