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Record W3116264770 · doi:10.1109/lcomm.2020.3046644

Outage Analysis of NOMA-Based Multiple-Antenna Hybrid Satellite-Terrestrial Relay Networks

2020· article· en· W3116264770 on OpenAlexaff
Lve Han, Wei‐Ping Zhu, Min Lin

Bibliographic record

VenueIEEE Communications Letters · 2020
Typearticle
Languageen
FieldEngineering
TopicSatellite Communication Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer scienceRelaySingle antenna interference cancellationNomaInterference (communication)Antenna (radio)SatelliteCommunications satelliteComputer networkOutage probabilityTelecommunicationsTopology (electrical circuits)Electronic engineeringPower (physics)FadingTelecommunications linkElectrical engineeringDecoding methodsEngineering

Abstract

fetched live from OpenAlex

In this letter, the outage performance of a novel non-orthogonal multiple access (NOMA)-based hybrid satellite-terrestrial relay network (HSTRN) is analyzed, where the satellite can directly communicate with one user while communicating with the other user only through an amplify-and-forward (AF) multiple-antenna relay. Exact and asymptotic outage probabilities of both users are derived by considering both fixed gain (FG) and variable gain (VG) AF relaying protocols, along with practical imperfect successive interference cancellation (I-SIC). Numerical results are provided to validate our analysis and unveil some useful engineering insights, such as the impacts of I-SIC, the number of antennas and the choice of relaying protocols on the system performance.

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)
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 score0.517
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.055
GPT teacher head0.255
Teacher spread0.200 · 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

Citations18
Published2020
Admission routes1
Has abstractyes

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