An Empirical Study of the Probability Density Function of Hf Noise

Abstract

To many, high-frequency (HF) radio communications is obsolete in this age of longdistance satellite communications and undersea optical fiber. Yet despite this, the HF band is used by defense agencies for backup communications and spectrum surveillance, and is monitored by spectrum management organizations to enforce licensing. Such activity usually requires systems capable of locating distant transmitters, separating valid signals from interference and noise, and recognizing signal modulation. Our research targets the latter issue. The ultimate aim is to develop robust algorithms for automatic modulation recognition of real HF signals. By real, we mean signals propagating by multiple ionospheric modes with co-channel signals and non-Gaussian noise. However, many researchers adopt Gaussian noise for their modulation recognition algorithms for the sake of convenience at the cost of accuracy. Furthermore, literature describing the probability density function (PDF) of HF noise does not abound. So we describe a simple empirical technique, not found in the literature, that supports our work by showing that the probability density function (PDF) for HF noise is generally not Gaussian. In fact, the probability density function varies with the time of day, electro-magnetic environment, and state of the ionosphere.

Software Define Radio System for HF Noise Measurements

“…• Some recent studies [2], [3] have reconfirmed that in the high-frequency (HF) band, the assumption of Gaussian noise is not always valid, since noise in this band is strongly affected by impulsive atmospheric radiators, such as lightning. It appears that a modified Bi-Kappa distribution is better suited for modelling such noise.…”

Automatic modulation classification of digital modulations in presence of HF noise

“…An automatic modulation classifier (AMC) is an essential part of a multi-standard communication system as it allows blind detection of the modulation schemes present in the received signal. However, designing an AMC for HF systems is not a trivial task, as the transmit signal is severely distorted due to ionospheric effects, multipath propagation, and non-Gaussian timevarying noise [2][3][4]. The non-Gaussian and time-varying nature of HF noise is a recent observation [3].…”

“…However, designing an AMC for HF systems is not a trivial task, as the transmit signal is severely distorted due to ionospheric effects, multipath propagation, and non-Gaussian timevarying noise [2][3][4]. The non-Gaussian and time-varying nature of HF noise is a recent observation [3]. It has been noted in [4] that the HF noise follows Gaussian (G) or Bi-kappa (BK) distributions depending on day time.…”

“…It has been noted in [4] that the HF noise follows Gaussian (G) or Bi-kappa (BK) distributions depending on day time. A BK distribution function is defined mathematically as [3] …”

“…Practical values of these parameters are σ = 46, k = 1.1 and σ = 20, k=1 [3]. Till now, designing AMC algorithms in presence of non-Gaussian noise has not received sufficient attention.…”