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Record W3022170906 · doi:10.1109/tvt.2020.3044837

Non-Orthogonal Multiple Access for Hybrid VLC-RF Networks With Imperfect Channel State Information

2020· preprint· en· W3022170906 on OpenAlexaff
Ahmed Al Hammadi, Paschalis C. Sofotasios, Sami Muhaidat, Mahmoud Al‐Qutayri, Hany Elgala

Bibliographic record

VenueIEEE Transactions on Vehicular Technology · 2020
Typepreprint
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsCarleton University
FundersKhalifa University of Science, Technology and Research
KeywordsVisible light communicationComputer scienceChannel state informationNomaOrthogonal frequency-division multiple accessWirelessRadio frequencyChannel (broadcasting)Electronic engineeringContext (archaeology)ImperfectComputer networkTelecommunicationsOrthogonal frequency-division multiplexingElectrical engineeringTelecommunications linkEngineering

Abstract

fetched live from OpenAlex

This paper proposes a general framework for the energy efficiency analysis of a hybrid visible light communication (VLC) and Radio Frequency (RF) wireless system, in which both VLC and RF subsystems utilize non-orthogonal multiple access (NOMA) technology. The proposed framework is based on realistic communication scenarios as it takes into account the mobility of users and assumes imperfect channel-state information (CSI). In this context, tractable closed-form expressions are derived for the corresponding average sum-rate of NOMA-VLC and orthogonal frequency division multiple access (OFDMA)-VLC. It is shown extensively that incurred CSI errors have a considerable impact on the average energy efficiency of both NOMA-VLC and OFDMA-VLC systems. Hence, they should be taken into detailed account in the design of practical systems. We further demonstrate that the average energy efficiency of the hybrid NOMA-VLC-RF system outperforms the NOMA-VLC system under imperfect CSI. Respective computer simulations corroborate the derived analytic results, and interesting theoretical and practical insights are provided, which will be useful in the effective design and deployment of conventional VLC and hybrid VLC-RF systems.

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 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), Research integrity
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 score0.901
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.003
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 head0.014
GPT teacher head0.233
Teacher spread0.219 · 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 teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations3
Published2020
Admission routes1
Has abstractyes

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