A Novel Blind Channel Identification and Equalisation AlgorithmBased on Maximum Likelihood
Wireless Personal Communications: An International Journal
Semi-blind equalization at the symbol rate with application to OFDM
Signal Processing
Blind Channel Identification Based on Noisy Observation by Stochastic Approximation Method
Journal of Global Optimization
Blind linear channel estimation using genetic algorithm and SIMO model
Signal Processing
Cyclostationarity: half a century of research
Signal Processing
Bibliography on cyclostationarity
Signal Processing
An evolutionary approach for joint blind multichannel estimation and order detection
EURASIP Journal on Applied Signal Processing
Joint power control and blind beamforming over wireless networks: a cross layer approach
EURASIP Journal on Applied Signal Processing
On blind MIMO system identification based on second-order cyclic statistics
Research Letters in Signal Processing
A New Approach of Blind Channel Identification in Frequency Domain
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Blind Deconvolution of Sources in Fourier Space Based on Generalized Laplace Distribution
International Journal of System Dynamics Applications
Hi-index | 754.84 |
In this communication, necessary and sufficient conditions are presented for the unique blind identification of possibly nonminimum phase channels driven by cyclostationary processes. Using a frequency domain formulation, it is first shown that a channel can be identified by the second-order statistics of the observation if and only if the channel transfer function does not have special uniformly spaced zeros. This condition leads to several necessary and sufficient conditions on the observation spectra and the channel impulse response. Based on the frequency-domain formulation, a new identification algorithm is proposed