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Record W3186648349 · doi:10.1109/jphot.2021.3098328

Robust Beamforming and Outage Performance of Uplink Multiuser Satellite-Aerial-Terrestrial Networks With Mixed RF-FSO Channels

2021· article· en· W3186648349 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

VenueIEEE photonics journal · 2021
Typearticle
Languageen
FieldEngineering
TopicOptical Wireless Communication Technologies
Canadian institutionsConcordia University
FundersShanghai Aerospace Science and Technology Innovation FoundationGovernment of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsTelecommunications linkBeamformingComputer scienceFadingRelayRobustness (evolution)Nakagami distributionChannel (broadcasting)Electronic engineeringChannel state informationRadio frequencyComputer networkTopology (electrical circuits)AlgorithmTelecommunicationsWirelessElectrical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

In this paper, we investigate the uplink transmission in a satellite-aerial-terrestrial network (SATN), where an aerial platform acts as an amplify-and-forward relay assisting the communication between multiple users and satellite. The users send messages to the aerial relay via radio frequency (RF) links, which are then forwarded to the satellite through a free-space optical (FSO) link. By assuming that the angle-of-arrival based imperfect channel state information of each user is known at the aerial platform, we propose a beamforming scheme to maximize the minimum average signal-to-interference-plus-noise ratio of the users. Due to the mathematical intractability, we design an iterative algorithm to obtain the optimal beamforming vector for the RF link. Furthermore, by considering that the FSO link experiences the Málaga fading with non-zero boresight pointing error and the RF links follow Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$m$</tex-math></inline-formula> fading, we derive an analytical expression for the outage probability of the considered SATN. Finally, computer simulation is conducted to validate our theoretical analysis. It is shown that the proposed algorithm can improve the system performance and robustness compared to existing works.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.024
GPT teacher head0.212
Teacher spread0.188 · 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