Hierarchical Learning for IRS-Assisted MEC Systems with Rate-Splitting Multiple Access

Intelligent reflecting surface (IRS)-assisted mobile edge computing (MEC) systems have shown notable improvements in efficiency, such as reduced latency, higher data rates, and better energy efficiency. However, the resource competition among users will lead to uneven allocation, increased latency,...

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Veröffentlicht in:	arXiv.org 2024-12
Hauptverfasser:	Wu, Yinyu, Zhang, Xuhui, Ren, Jinke, Shen, Yanyan, Yang, Bo, Wang, Shuqiang, Guan, Xinping, Niyato, Dusit
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Beamforming Computation offloading Decoding Deep learning Design optimization Edge computing Feature extraction Machine learning Mobile computing Multiple access Network latency Reconfigurable intelligent surfaces Resource allocation Splitting
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