LSTM-Based Trajectory and Phase-Shift Prediction for RSMA Networks Assisted by AIRS

This paper investigates rate-splitting multiple access (RSMA) networks with multiusers assisted by aerial intelligent reflecting surfaces (AIRS). To improve the sum-rate of the system, the UAV's trajectory and phase-shift vectors are optimized, in which the mobility scenarios with static and dy...

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Vydané v:	IEEE transactions on communications Ročník 72; číslo 11; s. 6929 - 6942
Hlavní autori:	Lima, Brena Kelly Sousa, Pedro Matos-Carvalho, Joao, Dinis, Rui, Benevides da Costa, Daniel, Beko, Marko, Oliveira, Rodolfo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.11.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Array signal processing Autonomous aerial vehicles Beamforming Heuristic algorithms Intelligent reflecting surface (IRS) Long short term memory long short-term memory (LSTM) Numerical models Phase shift precoder design rate-splitting multiple access (RSMA) Reconfigurable intelligent surfaces Resource management Sums Trajectory trajectory optimization unmanned aerial vehicle (UAV) Unmanned aerial vehicles Vectors
ISSN:	0090-6778, 1558-0857
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