Comparison of adaptive algorithms for multichannel adaptive equalizers. Application to underwater acoustic communications

Underwater acoustic digital communications are difficult because of the fading multipath nature of the channel. Adaptive equalization is known to highly improve the communication data rate by mitigating intersymbol interference (ISI). Multichannel equalizers are known to further improve the communication by a proper combination of the signals received on a sparse array. The major issue is to select an efficient receiver configuration. There are several parameters that may affect the quality of communication. In this paper, we focus on the main features that influence the performance of adaptive multichannel equalizers, such as the number and positioning of hydrophones, the length of the equalizer, the adaptive algorithm used to update the equalizer's tap gains. The relationship between the multipath structure of the channel and the multichannel receiver's performance is exhibited. Our analysis is performed on real data recorded on two different sea trials.

[1]  G. Jourdain,et al.  A fast self-optimized LMS algorithm for non-stationary identification: application to underwater equalization , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[2]  Luc Fety,et al.  MMSE antenna diversity equalization of a jammed frequency-selective fading channel , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[3]  J. Proakis,et al.  Adaptive multichannel combining and equalization for underwater acoustic communications , 1993 .

[4]  Lee Freitag,et al.  Efficient equalizer update algorithms for acoustic communication channels of varying complexity , 1997, Oceans '97. MTS/IEEE Conference Proceedings.

[5]  G. Jourdain,et al.  Adaptive multichannel equalizer for underwater communications , 1996, OCEANS 96 MTS/IEEE Conference Proceedings. The Coastal Ocean - Prospects for the 21st Century.

[6]  T. Kailath,et al.  Numerically stable fast transversal filters for recursive least squares adaptive filtering , 1991, IEEE Trans. Signal Process..

[7]  P. Balaban,et al.  Optimum diversity combining and equalization in digital data transmission with applications to cellular mobile radio II. Numerical results , 1992, IEEE Trans. Commun..