Deep Convolutional Linear Precoder Neural Network for Rate Splitting Strategy of Aerial Computing Networks

Aerial computing networks arefacing the challenge of massive node access, where user devices generally have stringent latency and robustness requirements. Rate Splitting Multiple Access (RSMA) is a general and robust multiple access framework for the aerial computing communication architecture, whic...

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Bibliographic Details
Published in:	IEEE transactions on network science and engineering Vol. 11; no. 6; pp. 5228 - 5243
Main Authors:	Wang, Zhijie, Ma, Ruhui, Shi, Hongjian, Cai, Zinuo, Lin, Liwei, Guan, Haibing
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.11.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adaptation models Aerial computing networks Artificial neural networks Communication Computational modeling Computing time Convolutional neural networks CSI feedback deep convolution neural network Design optimization Edge computing Feature extraction Feedback Information management linear precoder Messages Multiple access Network latency Neural networks Optimization Radio access networks rate splitting Receivers Splitting User requirements
ISSN:	2327-4697, 2334-329X
Online Access:	Get full text
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