Several engineering applications ranging from control to communications have to deal with a clipped Gaussian process, observed in the presence of Additive White Gaussian Noise (AWGN). For such a scenario, we derive in this paper a closed form expression of a Bayesian estimator, which recovers the original undistorted Gaussian process by minimizing the mean square estimation error. In addition, we use the obtained closed form expression to show that the Bayesian estimator results in a BitError Rate (BER) improvement compared to existing receivers for an Orthogonal Frequency Division Multiplexing (OFDM) system in an AWGN channel that is impaired by a clipping device at the transmitter.
Bayesian Estimation of Clipped Gaussian Processes with Application to OFDM
BANELLI, Paolo;
2002
Abstract
Several engineering applications ranging from control to communications have to deal with a clipped Gaussian process, observed in the presence of Additive White Gaussian Noise (AWGN). For such a scenario, we derive in this paper a closed form expression of a Bayesian estimator, which recovers the original undistorted Gaussian process by minimizing the mean square estimation error. In addition, we use the obtained closed form expression to show that the Bayesian estimator results in a BitError Rate (BER) improvement compared to existing receivers for an Orthogonal Frequency Division Multiplexing (OFDM) system in an AWGN channel that is impaired by a clipping device at the transmitter.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
