Identification of non-minimum phase linear stochastic systems
Automatica (Journal of IFAC)
Digital signal processing (3rd ed.): principles, algorithms, and applications
Digital signal processing (3rd ed.): principles, algorithms, and applications
Precoding and Signal Shaping for Digital Transmission
Precoding and Signal Shaping for Digital Transmission
Blind identification of FIR systems excited by discrete-alphabetinputs
IEEE Transactions on Signal Processing
Blind fractionally spaced equalization of noisy FIR channels: direct and adaptive solutions
IEEE Transactions on Signal Processing
MA estimation in polynomial time
IEEE Transactions on Signal Processing
A blind equalizer for nonstationary discrete-valued signals
IEEE Transactions on Signal Processing
FIR channel estimation through generalized cumulant slice weighting
IEEE Transactions on Signal Processing
Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters
IEEE Transactions on Fuzzy Systems
New criteria for blind deconvolution of nonminimum phase systems (channels)
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Blind identification and deconvolution of linear systems driven by binary random sequences
IEEE Transactions on Information Theory
Blind identification and equalization based on second-order statistics: a time domain approach
IEEE Transactions on Information Theory
Wireless Personal Communications: An International Journal
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Via the use of a zero forcing equalizer, the blind estimation of a finite impulse response (FIR), non-minimum phase (NMP) channel is discussed in this paper. Two efficient and reliable blind estimation algorithms are proposed here. One is based on the combination of second-order statistics (SOS) and the kurtosis property of the transmitted signal. The other utilizes the SOS information and the finite alphabet (FA) knowledge of the transmitted signal. SOS based methods provide efficient estimation of channel zeros from a very small number of samples, but the estimates are phase blind. The kurtosis property and the FA information can be used to resolve the ambiguity in system zero location. It is also shown that the equalizer output could be exploited recursively to improve the estimation accuracy using the FA property. As all the available information are used, the proposed methods achieve a very high accuracy in blind channel estimation. Performance of the estimation methods is also discussed. As the method inherently uses an equalizer, separate equalization is not necessary.