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Record W7017278145

Adaptation des taux et des puissances de transmission pour
\nles schémas IncrementaI Redundancy HARQ tronqués.

2013· dissertation· fr· W7017278145 on OpenAlexaboutno aff

Bibliographic record

VenueEspaceINRS (National Institute for Scientific Research (Canada)) · 2013
Typedissertation
Languagefr
FieldEconomics, Econometrics and Finance
TopicCredit Risk and Financial Regulations
Canadian institutionsnot available
Fundersnot available
KeywordsRedundancy (engineering)Domain (mathematical analysis)Social impact
DOInot available

Abstract

fetched live from OpenAlex

C'est en aveu du succès de ce mémoire que mes sincères mercis se vouent à mon directeur de recherche Prof. Leszek Szczecinski, professeur à l'INRS-EMT, pour sa serviabilité, ses compétences et ses directives fructueuses qu'il n'a cessé de me prodiguer tout au long de ce mémoire.Je tiens également à présenter mes sincères remerciements à Prof. Fabrice Labeau, mon co-superviseur et professeur à McGill, pour sa collaboration, son soutien et ses conseils pertinents durant nos réunions.J'adresse aussi ma profonde gratitude à tous mes amis, à ma famille et particulièrement à ma chère mère, mon cher père, mes deux frères Ahmed et Anes et à Hichem Garbouj qui ont été toujours présents pour moi contribuant ainsi à la réussite de ce mémoire.Finalement, je remercie mes collègues à l'INRS, Mohamed Jabi, Rabî Meftehi et Achref Methenni, que j'ai côtoyés au quotidien pendant ces deux dernières années, pour leur aide, leurs remarques, et leurs conseils qui ont été pour moi d'un grand apport. Imene Ben Salem Leszek SzczecinskiListe des acronymes -3GPP 3 rd Generation Partnership Project -ACK Acknowledgement -AMC Adaptative Modulation and Coding -ARQ Automatic Repeat reQuest -AWGN Additive White Gaussian Noise -CC Chase Combining -CRC Cyclique Redundancy Check -CSI Channel State Information -CSIR Channel State Information at the Receiver -CSIT Channel State Information at the Transmitter -dB décibel -DP Dynamic Programming -EDGE Enhanced Data Rates for GSM Evolution -FEC Forward Error Correction -FSMC Finite-State Markov Channel -GPRS General Packet Radio Service -HARQ Hybrid Automatic Repeat reQuest -IEEE Institute of Electrical and Electronics Engineers -IR Incremental Redundancy -LTE Long Term Evolution -MAC Medium Access Control -NACK Negative Acknowledgement -OSI Open Systems Interconnection -QoS Quality of Service -RCPC Rate-Compatible Punctured Convolutional codes -SNR Signal-to-Noise Ratio VI -Tep Transmission Control Protocol -TDMA Time Division Multiple Access -WiMAX Worldwide Interoperability for Microwave Access vii

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.034
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0100.013
Open science0.0040.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0190.012

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 head0.100
GPT teacher head0.333
Teacher spread0.233 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2013
Admission routes1
Has abstractyes

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