Statistical analysis and modeling of low-frequency radio noise and improvement of low-frequency communications

The objective of this work is the statistical characterization and modeling of atmospheric radio noise in the range 10 Hz {dollar}-{dollar} 60 kHz (denoted low-frequency noise), with the specific goal of improving communication systems operating in this range. The statistics analyzed include seasonal and diurnal variations, amplitude probability distributions (APDs), impulse interarrival time distributions, background noise statistics, and power spectral densities; the analyses are based on many thousands of hours of measurements made by the Stanford Radio Noise Survey System.; A number of noise models which accurately represent low-frequency noise APDs are compared, and two of the simplest models (i.e., each with only two parameters) are found to give extremely good performance in general. These are the Hall and alpha-stable (or {dollar}alpha{dollar}-stable) models, both of which approximate the Rayleigh distribution for low amplitude values but decay with an inverse power law for high amplitude values. It is concluded that the Hall model is the optimal choice in terms of accuracy and simplicity for locations exposed to heavy sferic activity, and the {dollar}alpha{dollar}-stable model is best for locations relatively distant from heavy sferic activity.; Based on the statistical characteristics of the noise data, a new clustering Poisson atmospheric noise model is developed. This model is based on several previously known statistical-physical models, but in addition takes into account the clustering of sferic impulses. It is shown that the clustering model accurately predicts the statistical features found in low-frequency radio noise data.; Finally, the bit error rate (BER) performance of receivers specifically designed for {dollar}alpha{dollar}-stable noise is compared with the BER performance of conventional low-frequency receivers. The communication signal formats examined are quadrature phase shift keying (QPSK) and 16 point quadrature amplitude modulation (16QAM). Hundreds of simulations using time-series data from various times and locations and at various center frequencies and bandwidths are performed, and the following results are found uniformly: for QPSK signals, virtually no performance improvement is gained when using an {dollar}alpha{dollar}-stable receiver instead of the best conventional receiver, but for 16QAM signals, an improvement of several dB is gained by using an {dollar}alpha{dollar}-stable receiver.