Neural Network-Based Wiener-Hammerstein Model for the Cancellation of Self-Interference in FDD Systems
Author:
Affiliation:
1. School of Electronics and Communication Engineering, Shenzhen Campus of Sun Yat-sen University,Shenzhen,China
Funder
Shenzhen Science and Technology Program
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10602771/10602729/10603173.pdf?arnumber=10603173
Reference11 articles.
1. Modeling and Joint Mitigation of TX and RX Nonlinearity-Induced Receiver Desensitization
2. Spline-Based Adaptive Cancellation of Even-Order Intermodulation Distortions in LTE-A/5G RF Transceivers
3. Cascaded Spline-Based Models for Complex Nonlinear Systems: Methods and Applications
4. A Neural Network Approach for the Cancellation of the Second-Order-Intermodulation Distortion in Future Cellular RF Transceivers
5. An Adaptive Machine Learning Based Approach for the Cancellation of Second-Order-Intermodulation Distortions in 4G/5G Transceivers
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