Bayesian techniques for blind deconvolution
Copyright policy )Bayesian techniques for blind deconvolution
The paper presents a new algorithm for blind deconvolution in digital communication which performs joint input and channel estimation. The blind deconvolution problem is formulated as a nonlinear and non-Gaussian fixed-lag mean square error filtering problem, and the extended Bayesian filter is derived as a suboptimal recursive estimator. Extensive simulations characterizing the performance of the filter in severe intersymbol interference channels are presented.
- Purdue University System United States
- Purdue University West Lafayette United States
blind deconvolution, Digital control/observation systems, input and channel estimation, nonlinear non-Gaussian fixed-lag mean square error filtering, suboptimal recursive estimator, Filtering in stochastic control theory
blind deconvolution, Digital control/observation systems, input and channel estimation, nonlinear non-Gaussian fixed-lag mean square error filtering, suboptimal recursive estimator, Filtering in stochastic control theory
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