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  4. Hidden node-aware dynamic spectrum access using deep learning for coexisting aeronautical communication systems
 
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Hidden node-aware dynamic spectrum access using deep learning for coexisting aeronautical communication systems

Publikationstyp
Conference Paper
Date Issued
2023-10
Sprache
English
Author(s)
Schulz, Leonard Paul  
Nachrichtentechnik E-8  
Kopyto, David Jonas  
Nachrichtentechnik E-8  
Stolpmann, Daniel  orcid-logo
Kommunikationsnetze E-4  
Lindner, Sebastian 
Kommunikationsnetze E-4  
Bauch, Gerhard  
Nachrichtentechnik E-8  
Timm-Giel, Andreas  orcid-logo
Kommunikationsnetze E-4  
TORE-URI
https://hdl.handle.net/11420/45119
Citation
IEEE 97th Vehicular Technology Conference (VTC 2023 Fall)
Contribution to Conference
IEEE 97th Vehicular Technology Conference, VTC 2023 Fall  
Publisher DOI
10.1109/VTC2023-Fall60731.2023.10333681
Scopus ID
2-s2.0-85181167988
Publisher
IEEE
We propose a novel approach based on deep learning to address the hidden node problem which occurs in the coexistence of aeronautical communication standards. The modern aeronautical communication standard L-band Digital Aeronautical Communications System (LDACS) in Air-Air (A/A) mode needs to share spectrum with the Distance Measuring Equipment (DME), which is a legacy system. As DME is safety-critical, causing interference on it must be avoided for all newly proposed aeronautical systems spectrally coexisting with it. Recently, cognitive radio techniques have been proposed for LDACS A/A to access spectrum dynamically and to overcome the limitations of static approaches. For this, a Recurrent Neural Network (RNN) was trained to predict idle time slots on those frequency bands, where both systems operate. By exploiting patterns in the spectrum access of DME, a promising amount of idle resources could be predicted. However, previous approaches would perform poorly in a real-world deployment, as they did not take the hidden node problem into account.This paper formulates the hidden node problem for the case that an LDACS A/A user is within communication range of a DME ground station, but not within range of all airborne DME users connected to it. Through statistical analysis, we underline the problem's significance in practical cases. We simulate the coexistence of the two systems from a channel access perspective, taking signal propagation and the behavior of the ground station into account. Further, we present an RNN that is able to predict the channel access of hidden nodes. The key idea of our algorithm is to exploit the fact that while DME request pulses from airborne users may appear as hidden, response pulses from the ground station will be visible. Our results show that by inferring DME request channel activity from the response channel, the hidden node problem can be overcome effectively. By using our approach, nearly the same performance can be achieved as in the idealized case where all nodes are visible.
Subjects
aeronautical communications
coexistence
cognitive radio
dynamic spectrum access
hidden node problem
MLE@TUHH
DDC Class
380: Commerce, Communications, Transport
Funding(s)
I³-Project - Machine Learning in Aeronautical Communications  
TUHH
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