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Record W4402661218 · doi:10.1109/tbc.2024.3434731

Next-Gen Satellite System: Integrative Non-Orthogonal Broadcast and Unicast Services Based on Innovative Frequency Reuse Patterns

2024· article· en· W4402661218 on OpenAlexaff
Weixiao Meng, Cheng Li

Bibliographic record

VenueIEEE Transactions on Broadcasting · 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
KeywordsUnicastReuseMultimedia Broadcast Multicast ServiceFrequency reuseTelecommunicationsComputer scienceDigital Video BroadcastingSatelliteSatellite systemCommunications satelliteDigital audio broadcastingSingle-frequency networkComputer networkBroadcasting (networking)Satellite broadcastingMulticastEngineeringGlobal Positioning SystemGNSS applicationsTransmission (telecommunications)

Abstract

fetched live from OpenAlex

The multibeam satellite system is crucial for providing seamless and various information services, such as broadcast and unicast messages. However, catering to the burgeoning number of users within a limited spectrum of resources presents formidable challenges. Therefore, we devise the non-orthogonal broadcast and unicast (NOBU) joint transmission framework using rate-splitting multiple access (RSMA), which leverages non-orthogonal transmission and precoding strategies. Furthermore, amalgamating traditional precoding with frequency reuse techniques, we propose two novel distributed frequency reuse (DFR) and centralized frequency reuse (CFR) strategies. Taking satellite beam gain characteristics and interference tolerance threshold into consideration, we further propose another two expansions of DFR and CFR strategies with innovative inner and outer divisions. For the NOBU joint transmission based on four novel frequency reuse patterns, we maximize the weighted sum rate (WSR). Subsequently, we introduce an improved alternating optimization algorithm, adept at converting intricate non-convex problems into tractable convex counterparts. Simulation outcomes demonstrate that our proposed schemes have significant improvements in WSR performance and are promising for various practical applications.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.829
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.244
Teacher spread0.223 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on BroadcastingSame topicSatellite Communication SystemsFrench-language works237,207