Title :
Robust Equalization of Mobile Underwater Acoustic Channels
Author :
Pelekanakis, Konstantinos ; Chitre, Mandar
Author_Institution :
Centre for Maritime Res. & Experimentation, La Spezia, Italy
Abstract :
Several underwater acoustic channels exhibit impulsive ambient noise. As a consequence, communication receivers implemented on the basis of the Gaussian noise assumption may yield poor performance even at moderate signal-to-noise ratios (SNRs). This paper presents a new channel-estimate-based decision feedback equalizer (CEB-DFE) that deals with high platform mobility, exploits any sparse multipath structure, and maintains robustness under impulsive noise. The key component of this DFE is a linear-complexity sparse channel estimator, which has the ability to detect and reject impulses based on two noise models: contaminated Gaussian and symmetric alpha stable (SαS). By processing phase-shift keying (PSK) signals from three mobile shallow-water acoustic links, the gain of the proposed receiver over existing equalizers is demonstrated.
Keywords :
Gaussian noise; channel estimation; decision feedback equalisers; equalisers; impulse noise; mobile communication; phase shift keying; underwater acoustic communication; wireless channels; CEB-DFE; Gaussian noise assumption; PSK signals; channel-estimate-based decision feedback equalizer; communication receivers; contaminated Gaussian noise model; high platform mobility; impulsive ambient noise; linear-complexity sparse channel estimator; mobile shallow-water acoustic links; mobile underwater acoustic channels; phase-shift keying signals; robust equalization; signal-to-noise ratios; sparse multipath structure; symmetric alpha stable noise models; Channel estimation; Decision feedback equalizers; Least squares approximation; Phase shift keying; Receivers; Robustness; Underwater acoustics; Affine projection sign algorithm (APSA); Doppler compensation; improved-proportionate normalized least mean squares (IPNLMS); interpolation; motion synchronization; normalized least mean squares (NLMS); outliers; recursive least squares (RLS); resampling; sparse equalization;
Journal_Title :
Oceanic Engineering, IEEE Journal of
DOI :
10.1109/JOE.2015.2469895