# Models of HF Interference over Cyprus
## 1 Introduction  
Interference poses one of the most crucial operating challenges on HF (formally defined to extend from 3 to 30 MHz) communication systems as a result of the long-distance HF propagation characteristics. This becomes more severe during nighttime conditions due to the reduction of the operating range of HF frequencies within which HF systems can operate because of the absence of solar activity, which does not support a sufficient ionospheric ionization level. This limiting aspect during the evening hours is crucially challenging for HF military systems such as spread spectrum and NVIS (Near Vertical Incidence Skywave) which are in need of updated information on interference conditions. The temporal characteristics of HF interference are depicted by the systematic diurnal and seasonal variability features of HF spectral occupancy at a particular geographic location. This systematic behavior is due to the fact that users adjust their transmission schedules and frequencies in accordance with ionospheric variability. Various past experiments resulted in datasets that contributed to the investigation of this detrimental factor for specific types of users (e.g., broadcast users) and applications (e.g., OTHR, Over The Horizon Radar) [1, 2]. Other HF spectral occupancy studies resulted in extended datasets on the basis of which congestion model specifications have been developed exploiting time-series and non-linear regression modeling approaches, as well as existing ionospheric models coupled with ray tracing [3, 4, 5]. One example of a long-term study is the HF spectral occupancy project at the University of Manchester, which has resulted in a twenty-year dataset of systematic HF interference measurements during stable daytime and nighttime ionospheric conditions from five monitoring sites over northern Europe. The outcome of this effort was a model specification known as the Laycock-Gott occupancy model [6]. Attempts have also been made, using other datasets, to apply neural networks (NN) to modeling the single allocation diurnal HF spectral occupancy [7], in the lower segment ofthe HF spectrum (4 MHz), focusing on groundwave users for long-term prediction [8] and short-term forecasting [9], with a focus on a single user type (broadcast users) [10], and for the entire HF spectrum [11].  
This paper describes a comparison in the application of non-linear regression modeling similar to the Laycock-Gott approach and NN on a one-year dataset of electric field measurements received by a low-elevation angle antenna over Cyprus. These models provide a tool to quantitatively assess the expected HF spectral occupancy for a specific user type and frequency range over the eastern Mediterranean to enhance the capability of a HF communication system operator to evaluate the HF interference background under benign ionospheric conditions (i.e., under quiet geomagnetic activity). The dataset was collected by a dedicated HF monitoring system operating in Cyprus with a focus on the measurement and analysis of specific attributes expected to affect HF spectral congestion, such as antenna elevation angle, bandwidth, and azimuth [12]. The purpose of this study is to exploit more than a year of HF electric field measurements from the low-elevation calibrated monopole HF antenna to develop single-allocation HF spectral congestion models using neural networks and non-linear regression model specifications and compare these approaches.