GMM-based Symbol Error Rate Prediction for Multicarrier Systems with Impulsive Noise Suppression
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Theoretical analysis of orthogonal frequency division multiplexing (OFDM) systems equipped at the receiver by a non-linear impulsive noise suppressor is a challenging topic in communication systems. Indeed, although an exact closed-form expression for the output signal-to-noise ratio (SNR) of such OFDM systems is available for widely used impulsive noise models, theoretical analysis of the associated symbol error rate (SER) is still open. So far, the analytical SER expressions available in the literature approximate the time-domain impulsive noise, as Gaussian distributed in the discrete frequency domain. Conversely, this work presents an accurate analysis of the distortion noise at the nonlinearity output exploiting a Gaussian mixture model (GMM). By using GMMs we unified the approach of SER prediction for unmitigated systems, as well as for the mitigated ones, equipped by non-linear impulsive noise suppressors, including blanking, clipping, clipping-blanking and attenuating processors. Closed form expressions for the SER are derived both for non-fading and frequency-selective Rayleigh and Rician fading channels affected by impulsive noise which is represented by GMMs, thus including Bernoulli-Gaussian (BG), Middleton Class-A, as well as (approximated) alpha-stable noise. Theoretic SER performance are compared with simulations, showing very good agreement for all the impulsive noise scenarios and the non-linear suppressors.
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