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Record W4404788139 · doi:10.1109/jiot.2024.3506947

Multiple Access Strategy for Complex Integrated Satellite-Terrestrial Networks of Multiconstraint and Multicooperation Modes

2024· article· en· W4404788139 on OpenAlexaff
Shuai Han, Zhiqiang Li, Abderrahim Benslimane, Cheng Li

Bibliographic record

VenueIEEE Internet of Things Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicSatellite Communication Systems
Canadian institutionsSimon Fraser University
FundersChongqing Municipal Key Laboratory of Institutions of Higher EducationNational Natural Science Foundation of China
KeywordsComputer scienceConstraint (computer-aided design)SatelliteSatellite broadcastingCommunications satelliteComputer networkDistributed computingTelecommunications

Abstract

fetched live from OpenAlex

Integrated satellite-terrestrial networks (ISTNs) are increasingly recognized for their global communication. However, the existing research mainly focuses on simplified ISTNs, where cooperative strategies between satellites and base stations (BSs) are not easily applicable to real-world scenarios. There is a pressing need to investigate more realistic and complex ISTNs to address this gap. To address this gap, we investigate a more realistic and complex ISTN configuration, characterized by a large number of BSs, each divided into interference and service areas. Based on two cooperative modes, i.e., overlay and underlay spectrum sharing, two multiple access schemes are proposed for complex ISTNs using promising rate-splitting technology. These schemes consider multiple constraints simultaneously, such as communication delay, information rate, and power limit. Furthermore, a delay-rate adaptive user grouping strategy is proposed according to communication delay and information rate. For these schemes, the corresponding weighted sum rate problems are formulated, and an improved alternating optimization (AO) method is designed to solve the nonconvex challenges in two spectrum sharing modes. Moreover, a satellite-terrestrial coordinated iteration strategy based on AO is proposed to reduce the computational complexity in underlay spectrum sharing. Simulation outcomes confirm the advantages of our proposed schemes compared to various standard schemes.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.626
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.092
GPT teacher head0.323
Teacher spread0.231 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2024
Admission routes1
Has abstractyes

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