We consider the problem of estimating correlated Gaussian samples in (correlated) impulsive noise, through message-passing algorithms. This is a meaningful theoretical framework to model signal transmission on power-line communication systems. Due to the mixture of Gaussian variables (the samples) and Bernoulli variables (the impulsive noise switches), the complexity of messages increases exponentially with the number of samples. By adopting a Parallel Iterative Scheduling, with properly constrained messages, it turns out that each iteration of the proposed algorithm is equivalent to the parallel run of a classical Kalman Smoother and a binary sequence detection through the BCJR algorithm. Results demonstrate the effectiveness of the receiver along with its performance, in terms of mean square estimation error.

Estimation of a Gaussian Source with Memory in Bursty Impulsive Noise / Vannucci, Armando; Colavolpe, Giulio; Pecori, Riccardo; Veltri, Luca. - ELETTRONICO. - (2019), pp. 60-65. (Intervento presentato al convegno 23rd IEEE International Symposium on Power Line Communications and its Applications, ISPLC 2019 tenutosi a Prague; Czech Republic nel 2019) [10.1109/ISPLC.2019.8693453].

Estimation of a Gaussian Source with Memory in Bursty Impulsive Noise

Vannucci, Armando;Colavolpe, Giulio;Pecori, Riccardo;Veltri, Luca
2019-01-01

Abstract

We consider the problem of estimating correlated Gaussian samples in (correlated) impulsive noise, through message-passing algorithms. This is a meaningful theoretical framework to model signal transmission on power-line communication systems. Due to the mixture of Gaussian variables (the samples) and Bernoulli variables (the impulsive noise switches), the complexity of messages increases exponentially with the number of samples. By adopting a Parallel Iterative Scheduling, with properly constrained messages, it turns out that each iteration of the proposed algorithm is equivalent to the parallel run of a classical Kalman Smoother and a binary sequence detection through the BCJR algorithm. Results demonstrate the effectiveness of the receiver along with its performance, in terms of mean square estimation error.
2019
9781728102894
Estimation of a Gaussian Source with Memory in Bursty Impulsive Noise / Vannucci, Armando; Colavolpe, Giulio; Pecori, Riccardo; Veltri, Luca. - ELETTRONICO. - (2019), pp. 60-65. (Intervento presentato al convegno 23rd IEEE International Symposium on Power Line Communications and its Applications, ISPLC 2019 tenutosi a Prague; Czech Republic nel 2019) [10.1109/ISPLC.2019.8693453].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2859826
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