Model-Driven Deep Learning-Based MIMO-OFDM Detector: Design, Simulation, and Experimental Results-Reference-Cited by-同舟云学术

Model-Driven Deep Learning-Based MIMO-OFDM Detector: Design, Simulation, and Experimental Results

Author:

Zhou Xingyu¹^ORCID,Zhang Jing¹^ORCID,Syu Chen-Wei²,Wen Chao-Kai²^ORCID,Zhang Jun³^ORCID,Jin Shi¹^ORCID

Affiliation:

1. National Mobile Communications Research Laboratory, Southeast University, Nanjing, China

2. Institute of Communications Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan

3. College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China

Funder

National Key Research and Development Program

National Natural Science Foundation of China

Ministry of Science and Technology of Taiwan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

Reference36 articles.

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3. 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