Hybrid-Layers Neural Network Architectures for Modeling the Self-Interference in Full-Duplex Systems
Author:
Affiliation:
1. Faculty of Engineering and Applied Science, Memorial University, St. John’s, NL, Canada
2. Huawei Canada Research Centre, Huawei Technologies Canada Co., Ltd., Ottawa, ON, Canada
Funder
Huawei Canada Research Centre
Huawei Technologies
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/25/9805757/09736621.pdf?arnumber=9736621
Reference41 articles.
1. A 5G-Enabling Technology: Benefits, Feasibility, and Limitations of In-Band Full-Duplex mMIMO
2. Hybrid Time-Switching and Power Splitting SWIPT for Full-Duplex Massive MIMO Systems: A Beam-Domain Approach
3. Low Complexity Neural Network Structures for Self-Interference Cancellation in Full-Duplex Radio
4. Hardware Implementation of Neural Self-Interference Cancellation
5. Design and Implementation of a Neural Network Aided Self-Interference Cancellation Scheme for Full-Duplex Radios
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