Reservoir Computing Meets Extreme Learning Machine in Real-Time MIMO-OFDM Receive Processing

Author:

Li Lianjun1ORCID,Liu Lingjia1ORCID,Zhou Zhou1,Yi Yang1ORCID

Affiliation:

1. Bradley Department of Electrical and Computer Engineering, Wireles@Virginia Tech, Virginia Tech, Blacksburg, VA, USA

Funder

US National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Cited by 11 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. Enhancing Driving Behavior Analysis in Autonomous Systems: A Reservoir Computing and Temporal-Aware Machine Learning Approach;2024 IEEE International Conference on Mobility, Operations, Services and Technologies (MOST);2024-05-01

2. Efficient Channel Coding and Error Correction in MIMO-OFDM by Using Spatio Temporal Joint Graph Convolutional Networks;2024 Fourth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT);2024-01-11

3. Real-Time Machine Learning for Multi-User Massive MIMO: Symbol Detection Using Multi-Mode StructNet;IEEE Transactions on Wireless Communications;2023-12

4. Online Learning Meets Semantic Communication over Wireless Channels;MILCOM 2023 - 2023 IEEE Military Communications Conference (MILCOM);2023-10-30

5. Theoretical Foundation and Design Guideline for Reservoir Computing-Based MIMO-OFDM Symbol Detection;IEEE Transactions on Communications;2023-09

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