English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Theoretical analysis of orthogonal frequency division multiplexing (OFDM)systems equipped at the receiver by a non-linear impulsive noise suppressor isa challenging topic in communication systems. Indeed, although an exactclosed-form expression for the output signal-to-noise ratio (SNR) of such OFDMsystems is available for widely used impulsive noise models, theoreticalanalysis of the associated symbol error rate (SER) is still open. So far, theanalytical SER expressions available in the literature approximate thetime-domain impulsive noise, as Gaussian distributed in the discrete frequencydomain. Conversely, this work presents an accurate analysis of the distortionnoise at the nonlinearity output exploiting a Gaussian mixture model (GMM). Byusing GMMs we unified the approach of SER prediction for unmitigated systems,as well as for the mitigated ones, equipped by non-linear impulsive noisesuppressors, including blanking, clipping, clipping-blanking and attenuatingprocessors. Closed form expressions for the SER are derived both for non-fadingand frequency-selective Rayleigh and Rician fading channels affected byimpulsive 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 goodagreement for all the impulsive noise scenarios and the non-linear suppressors.

GMM-based Symbol Error Rate Prediction for Multicarrier Systems with Impulsive Noise Suppression