By Topic

MMSE-Lattice Sequential Equalization of Underwater Acoustic Channels

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Green, D. ; Teledyne-Benthos Inc., Falmouth ; Damen, M.O.

Underwater acoustic communications is today accomplished with a variety of modulation techniques, including both non-coherent and coherent methods, each shown to perform "best" under certain environmental and operational constraints. Coherent communications typically involve a form of M-ary phase shift keyed (MPSK) signaling, combined with one of a variety of channel equalization schemes at the receiver. The most common scheme is the mean square error minimization (MMSE) decision feedback equalizer (DFE), designed in part by Professors John Proakis and Milica Stojanovic and now extended by many developers for a variety of applications. Even though often effective, the performance of the DFE becomes far from the optimal performance that can be obtained by the maximum likelihood sequence estimator (MLSE). While aiming for the optimal performance, our interest is in the use of small, battery- powered, DSP-based devices which have fairly hard constraints on computer resources. We consider an older alternative to the DFE, the maximum likelihood sequence estimator (MLSE), usually implemented with a Viterbi algorithm. Referring to historical coding theory, it is well known that a sequential estimation alternative to MLSE-based decoding is "almost" as effective, given a modest increase in signal-to-noise ratio (SNR). Furthermore, the computational burden is usually far less than with the conventional Viterbi approach. The focus of this paper is on the development and application of a Fano Sequential Estimator acting as an alternative to the Viterbi algorithm for MLSE-based channel compensation.

Published in:

OCEANS 2007

Date of Conference:

Sept. 29 2007-Oct. 4 2007