Joint Detection and Self-Interference Cancellation in Full-Duplex Systems Using Machine Learning-Reference-Cited by-同舟云学术

Joint Detection and Self-Interference Cancellation in Full-Duplex Systems Using Machine Learning

Published:2021-10-31 Issue: Volume: Page:
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Container-title:2021 55th Asilomar Conference on Signals, Systems, and Computers
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Author:

Balatsoukas-Stimming Alexios¹

Affiliation:

1. Eindhoven University of Technology,Eindhoven,the Netherlands,5600 MB

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9723034/9723086/09723167.pdf?arnumber=9723167

Reference21 articles.

1. Digital Self-Interference Cancellation for Full Duplex Wireless Communication Based on Neural Networks

2. Performance Comparison of Real and Complex Valued Neural Networks for Digital Self-Interference Cancellation

3. Low complexity neural network structures for self-interference cancellation in full-duplex radio;elsayed;IEEE Communications Letters,2020

4. MIMO Full Duplex Radios with Deep Learning

5. Hybrid-layers neural network architectures for modeling the selfinterference in full-duplex systems;elsayed;IEEE Transactions on Vehicular Technology,2021

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1. Hypernetwork-Based Adaptive Self-Interference Cancellation for Full-Duplex Wireless Communication Systems;2024 IEEE International Conference on Communications Workshops (ICC Workshops);2024-06-09

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3. Machine Learning-Based Self-Interference Cancellation for Full-Duplex Radio: Approaches, Open Challenges, and Future Research Directions;IEEE Open Journal of Vehicular Technology;2024

4. CNN-Based Receiver Architecture for Full-Duplex MIMO Communication Systems;2023 11th International Japan-Africa Conference on Electronics, Communications, and Computations (JAC-ECC);2023-12-18

5. Joint Self-Interference Cancellation and Data Estimation for OFDM Based Full-Duplex Communication Systems;2023 57th Asilomar Conference on Signals, Systems, and Computers;2023-10-29