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Record W2291599761 · doi:10.1109/glocom.2015.7417507

Resource Allocation Framework in 5G Multi-Hop Relay System

2015· article· en· W2291599761 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

Venue2015 IEEE Global Communications Conference (GLOBECOM) · 2015
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsCommunications Research Centre CanadaUniversité du Québec à Montréal
Fundersnot available
KeywordsRelaySoftware deploymentComputer scienceArchitectureHop (telecommunications)Resource allocationComputer networkLTE AdvancedResource management (computing)Resource (disambiguation)Principal (computer security)Distributed computingTelecommunications linkComputer security

Abstract

fetched live from OpenAlex

Cellular relaying architecture is in an early stage for development and deployment. A restricted number of deployment scenarios are addressed in the LTE-A relay standard, though different design options in alternative deployment scenarios do potentially exist. Presently, the LTE-A relay standard is restricted to a single-hop relaying. The principal reason for opting for this architecture is to minimize system complexity. Nonetheless, multi-hop relay architecture could potentially provide greater capacity and coverage, in the future, particularly for urban sparse area deployment scenarios. However, many problems involving the complexity of multi-hop relaying paradigm need to be resolved, specifically resource management. In this paper, we focus on the resource management problem, and we propose a new resource allocation framework to overcome the additional challenges introduced by the multi-hop relay stations. Numerical results are presented to demonstrate the validity of the proposed framework.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science
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 score0.932
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0080.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.148
GPT teacher head0.358
Teacher spread0.209 · 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