Blind identification and equalization based on second-order statistics: a time domain approach

1994/03/01 by Lang Tong, Guanghan Xu, T. Kailath · 1,074 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #Algorithm #Blind Source Separation Techniques #Blind equalization #Channel (broadcasting) #Computer science #Convergence (economics) #Equalization (audio) #Fractal and DNA sequence analysis #Higher-order statistics #Identification (biology) #Mathematics #Multipath propagation #Signal processing #Speech and Audio Processing #Statistics #Telecommunications

paper · doi:10.1109/18.312157

published in IEEE Transactions on Information Theory 40(2), 340-349 (Institute of Electrical and Electronics Engineers)

openalex publication_date 1994/03/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Abstract

A new blind channel identification and equalization method is proposed that exploits the cyclostationarity of oversampled communication signals to achieve identification and equalization of possibly nonminimum phase (multipath) channels without using training signals. Unlike most adaptive blind equalization methods for which the convergence properties are often problematic, the channel estimation algorithm proposed here is asymptotically ex-set. Moreover, since it is based on second-order statistics, the new approach may achieve equalization with fewer symbols than most techniques based only on higher-order statistics. Simulations have demonstrated promising performance of the proposed algorithm for the blind equalization of a three-ray multipath channel.>

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