Sensoriamento Espectral Subaquático com Receptor por Conversão Direta sob Ruído α-Estável Simétrico e α-Sub-Gaussiano

Abstract

Spectrum sensing in underwater cognitive acoustic networks or in underwater acoustic sensor networks can be impaired by impulsive noise generated by snapping shrimps. In mathematical analysis or simulations, the amplitude variations of this noise are com monly modeled by the symmetric alpha-stable (SαS) distribution. As an alternative, the alpha-sub-Gaussian (αSG) distribution can model both temporal correlation and amplitude variations. This work evaluates the performance of underwater spectrum sensing with a direct-conversion receiver (DCR) under impulsive noise modeled by the SαS and αSG distributions. Several recent test statistics are compared, demons trating that they have different degrees of robustness against impulsive noise and that the DCR is significantly less sensitive to this noise, compared to the conventional re ceiver model that does not take into account the influences of hardware characteristics into the performance of spectrum sensing. It was verified that, in the absence of im pulsive noise, the DCR model, compared to the conventional one, causes performance degradation in all detectors due to the signal processing steps considered therein. In the presence of impulsive noise, it was unveiled that, regardless of the receiver model used, not modeling the temporal correlation makes the performance to be underestima ted for most detectors analyzed.The GID and PRIDe detectors exhibited meaningfully robustness against impulsive noise in the most realistic scenario, whereas the AVC and ED detectors showed expressive sensitivity.