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A Link Level Study on LDM for Mixed Broadcast-Broadband Service Delivery in 5G

2023· article· en· W4385871896 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTelecommunications and Broadcasting Technologies
Canadian institutionsCommunications Research Centre CanadaUniversity of Toronto
Fundersnot available
KeywordsBroadbandComputer scienceBroadband networksMultimedia Broadcast Multicast ServiceSingle-frequency networkComputer networkService (business)MultiplexingTransmission (telecommunications)BeamformingTelecommunicationsMulticast

Abstract

fetched live from OpenAlex

This paper addresses the use of Layered Division Multiplexing (LDM) as a method to deliver multiple services in 5G New Radio (NR). LDM is a technique that allows multiple services to be delivered over the same time-frequency resource by allocating transmission power between different layers. A two-layered LDM system can be implemented in 5G NR to deliver both Single Frequency Network (SFN) broadcast service and broadband service over a single time-frequency resource. The integration of 5G beamforming into LDM allows for the creation of sufficiently wide beams for SFN broadcast service and narrow beams for broadband service. Theoretical analysis and link level simulation demonstrate that this approach can provide both services with more spectral efficiency and energy saving.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.830
Threshold uncertainty score0.539

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 science0.0000.000
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 head0.093
GPT teacher head0.286
Teacher spread0.193 · 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