Paper Info
Title
Predicting the Occupancy of the HF Amateur Service with Neural Network Ensembles
Abstract
The Amateur Service is allocated approximately 3 MHz of spectrum in the HF band (3-30MHz) which is primarily used for long range communications via the ionosphere. However only a fraction of this resource is usually available due to unfavourable propagation conditions in the ionosphere imposed by solar activity on the HF channel. In this respect interference is considered a significant problem to overcome, in order to establish viable links at low transmission power. This paper presents the development of a set of Neural Network ensembles which can serve as a tool for predicting the likelihood of interference in the frequency allocations utilized by amateur users. The proposed approach successfully captures the temporal and long-term solar dependent variability of congestion, formally defined as the fraction of channels within a certain frequency allocation with signals exceeding a given threshold.
Year
DOI
Venue
2009
10.1007/978-3-642-04277-5_34
ICANN (2)
Keywords
Field
DocType
long-term solar dependent variability,hf band,hf amateur service,hf channel,frequency allocation,certain frequency allocation,neural network ensemble,amateur service,respect interference,amateur user,neural network ensembles,solar activity,ionosphere,spectrum
Computer science,Ionosphere,Mean squared error,Real-time computing,Occupancy,Interference (wave propagation),Artificial intelligence,Frequency allocation,Artificial neural network,Simulation,Amateur,Communication channel,Machine learning
Conference
Volume
ISSN
Citations 
5769
0302-9743
0
PageRank 
References 
Authors
0.34
6
2
Name
Order
Citations
PageRank
Harris Papadopoulos121926.33
Haris Haralambous2366.72