A novel cluster based MLSE equalizer for M-PAM signaling schemes

Authors:
Yannis Kopsinis;Sergios Theodoridis
Affiliations:
Department of Informatics and Telecommunications, University of Athens Panepistimioupolis, Ilissia 15784, Athens, Greece;Department of Informatics and Telecommunications, University of Athens Panepistimioupolis, Ilissia 15784, Athens, Greece
Venue:
Signal Processing
Year:
2003

Citing 10
Cited 4

Adaptive system identification and signal processing algorithms

Adaptive system identification and signal processing algorithms
Adaptive filter theory (3rd ed.)

Adaptive filter theory (3rd ed.)
Efficient clustering techniques for channel equalization in hostile environments

Signal Processing
Blind and semi-blind equalization using hidden Markov models and clustering techniques

Signal Processing - Special issue on current topics in adaptive filtering for hands-free acoustic communication and beyond
Why use Bayesian equalization based on finite data blocks?

Signal Processing - Special section on Markov Chain Monte Carlo (MCMC) methods for signal processing
Mobile Radio Communications

Mobile Radio Communications
Robustness of least-squares and subspace methods for blind channelidentification/equalization with respect to effective channelundermodeling/overmodeling

IEEE Transactions on Signal Processing
Channel equalization for coded signals in hostile environments

IEEE Transactions on Signal Processing
Rayleigh fading channels in mobile digital communication systems .I. Characterization

IEEE Communications Magazine
Time division multiple access methods for wireless personal communications

IEEE Communications Magazine

Robust joint channel and noise estimation in Bayesian blind equalizers

Signal Processing
Low complexity generalized EM algorithm for blind channel estimation and data detection in optical communication systems

Signal Processing - Special section: Distributed source coding
A novel efficient cluster-based MLSE equalizer for satellite communication channels with M-QAM signaling

EURASIP Journal on Applied Signal Processing
Low complexity as whole signal detection algorithm for frequency-selective fading channels

WTS'09 Proceedings of the 2009 conference on Wireless Telecommunications Symposium

Quantified Score

Hi-index	0.08

Visualization

Abstract

In this paper a new cluster based Maximum Likelihood Sequence Equalizer is presented. The novelty of the algorithm consists of a new technique for the estimation of all the centers around which the received observations are clustered. For a channel of order L and M-PAM signaling scheme, only L of the cluster centers need to be estimated, and the rest, ML - L, are subsequently computed via simple operations. This has a two-fold advantage compared to previously proposed cluster based algorithms. It reduces dramatically both the computational complexity and the required length of the training sequence. The new method is compared with the standard LMS and RLS based MLSE and the Bayesian RBF equalizer. Moreover, the overmodeling and the undermodeling cases are also explored. The results are very favorable for the new technique, from the computational as well as the performance point of view.