End-to-End Learning-Based Full-Duplex Amplify-and-Forward Relay Networks
Author:
Affiliation:
1. Department of Engineering and Physical Science (EPS), Heriot-Watt University, Edinburgh, U.K
2. Institute for Digital Communications, The University of Edinburgh, Edinburgh, U.K
Funder
U.K. Engineering and Physical Sciences Research Council
COG-MHEAR: Towards Cognitively-Inspired 5G IoT enabled, Multi-Modal Hearing Aids
Signal Procssing in the Information Age
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/26/10016736/09965433.pdf?arnumber=9965433
Reference51 articles.
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3. A Differential ML Combiner for Differential Amplify-and-Forward System in Time-Selective Fading Channels
4. Performance of Selection Combining for Differential Amplify-and-Forward Relaying Over Time-Varying Channels
5. Outage Analysis of Multihop Full Duplex Relaying
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