Predicting the diurnal variation of HF spectral occupancy over Sweden 
 
Haris Haralambous, Harris Papadopoulos, Lefteris Economou 
 
This paper presents the application of Neural Networks as a means of optimising 
the reliability of HF communication systems by predicting the detrimental effect 
of interference from other users and its variability due to the ionosphere. In 
particular, the development of a long-term interference prediction model for the 
HF spectrum is described. This model can be used in the absence of system 
capability to assess interference background in real time or near real time, to 
advise operators on typical interference occupancy levels and therefore assist 
in the planning of frequency usage and management. The dataset of diurnal 
occupancy measurements used for the model development was taken over a period of 
seven years (April 1994 to January 2000) at Linkoping and Kiruna (Sweden) in the 
frames of a long-term project being undertaken jointly by the University of 
Manchester and by the Swedish Defence Research Establishment, to measure 
systematically and to analyse the occupancy of the entire HF spectrum.