RF Canceller Tuning Acceleration Using Neural Network Machine Learning for In-Band Full-Duplex Systems

RF Canceller Tuning Acceleration Using Neural Network Machine Learning for In-Band Full-Duplex Systems

The fifth-generation wireless system framework provides the option to evaluate the performance of in-band full-duplex (IBFD) operation through flexible duplexing. The resulting self-interference, however, must be mitigated within a fraction of a symbol duration for successful communication. This pap...

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Bibliographic Details
Main Authors: Kenneth E. Kolodziej, Aidan U. Cookson, Bradley T. Perry
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Open Journal of the Communications Society
Subjects:
5G mobile communication
in-band full-duplex
machine learning
RF cancellation
self-interference cancellation
Online Access:https://ieeexplore.ieee.org/document/9431091/

Internet

https://ieeexplore.ieee.org/document/9431091/

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