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Record W2944857719 · doi:10.22215/etd/2018-13220

Number-Theoretic Sequence Design for Uncoordinated Resource Block Assignments in Relay-Assisted Machine-Type Communication Systems

2018· dissertation· en· W2944857719 on OpenAlex
Yaser M. M. Fouad

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicIoT Networks and Protocols
Canadian institutionsCarleton University
Fundersnot available
KeywordsSequence (biology)Set (abstract data type)Computer scienceBlock (permutation group theory)AlgorithmTheoretical computer scienceMathematicsCombinatorics

Abstract

fetched live from OpenAlex

Terminal relaying offers effective means for realizing machine-type communication (MTC) systems. However, coordinating these relaying terminals (RTs) becomes a cumbersome task as the number of RTs increases. In the absence of channel state information, the efficient utilization of RTs requires a mechanism by which RTs can autonomously assign available resource blocks (RBs) to large numbers of uncoordinated MTC devices with minimal conflicts. Unlike random RB assignments, using prescribed assignment sequences provides an opportunity for obtaining performance gains. However, realizing these gains requires optimizing RB assignments over a large set of sequences. One technique for selecting assignment sequences is based on an exhaustive search of exponential complexity over sequences generated by multiplicative cyclic groups. This technique restricts the RB assignment sequence length and does not consider sequences generated using other group operations.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.810
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0010.000
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 head0.032
GPT teacher head0.298
Teacher spread0.266 · 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

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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