Deep Learning-Based Dynamic Spectrum Access for Coexistence of Aeronautical Communication Systems-Reference-Cited by-同舟云学术

Deep Learning-Based Dynamic Spectrum Access for Coexistence of Aeronautical Communication Systems

Published:2022-09 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)
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Author:

Kopyto David¹,Lindner Sebastian²,Schulz Leonard¹,Stolpmann Daniel²,Bauch Gerhard¹,Timm-Giel Andreas²

Affiliation:

1. Hamburg University of Technology,Institute of Communications,Germany

2. Hamburg University of Technology,Institute of Communication Networks,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10012685/10012692/10012932.pdf?arnumber=10012932

Reference11 articles.

1. Modeling DME interference impact on LDACS1

2. Overview of interference situation and mitigation techniques for LDACS1

3. Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures;bergstra;30th International Conference on Machine Learning ICML,2013

4. European Organization for Civil Aviation Equipment (EUROCAE), Minimum Operational Performance Requirements for Distance Measuring Equipment Interrogator (DME/N and DME/P) Operating Within the Radio Frequency Range 960 to 1215 MHz,1987

5. Energy Detection Based Cooperative Spectrum Sensing in Cognitive Radio Networks

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