A Light-weight Learning Framework for RIS-assisted Beamforming Design with Mobile Edge Computing
Author:
Affiliation:
1. Shenzhen University,State Key Laboratory of Radio Frequency Heterogeneous Integration,Guandong,China,518060
2. Tanta University,Tanta,Egypt
3. Menoufia University,Faculty of Electronic Engineering,Menouf, Menoufia,Egypt
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10233255/10233122/10233545.pdf?arnumber=10233545
Reference17 articles.
1. Machine learning for intelligent-reflecting-surface-based wireless communication towards 6G: A review;sejan;SENSORS,2022
2. An Optimal Reflective Elements Grouping Model for RIS-Assisted IoT Networks Using Q-Learning
3. Smart Grid Enabled Computation Offloading and Resource Allocation for SWIPT-Based MEC System
4. Hybrid Evolutionary-based Sparse Channel Estimation for IRS-assisted mmWave MIMO Systems
5. Deep Reinforcement Learning Based Intelligent Reflecting Surface Optimization for MISO Communication Systems
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Unsupervised Learning for Joint Beamforming Design in RIS-Aided ISAC Systems;IEEE Wireless Communications Letters;2024-08
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