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Network Coding for<scp>D2D</scp>

2020· other· en· W3024336310 on OpenAlex

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

VenueWiley 5G Ref · 2020
Typeother
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsNetwork packetUser equipmentTelecommunications linkLinear network codingComputer networkBase stationComputer scienceCellular networkRelayCoding (social sciences)Mathematics

Abstract

fetched live from OpenAlex

Abstract For cellular downlink transmissions, we propose an approach leveraging cooperative device‐to‐device (D2D) communications and network coding (NC), which can substantially reduce the cellular resource consumption and the total energy consumption. In the proposed approach, the base station generates and broadcasts linear combinations based on the packets requested by different user equipments (UEs) until at least one UE can recover all the original packets, called mature UE. Then, a selected mature UE broadcasts new linear combinations based on the recovered original packets to neighbors via D2D until all UEs can decode their packets. A semi‐centralized cooperative control method is proposed for cellular uplink transmissions, where UE relays are randomly selected according to a certain density decided by the base station. Two specific cooperative approaches, i.e. the random UE relay approach and the NC approach, are proposed for D2D communications.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.294
Threshold uncertainty score1.000

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 science0.0020.001
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 head0.044
GPT teacher head0.274
Teacher spread0.230 · 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