Semi-blind SIMO flat-fading channel estimation in unknown spatially correlated noise using the EM algorithm
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The Department of Electrical and Computer Engineering (ECpE) contains two focuses. The focus on Electrical Engineering teaches students in the fields of control systems, electromagnetics and non-destructive evaluation, microelectronics, electric power & energy systems, and the like. The Computer Engineering focus teaches in the fields of software systems, embedded systems, networking, information security, computer architecture, etc.
History
The Department of Electrical Engineering was formed in 1909 from the division of the Department of Physics and Electrical Engineering. In 1985 its name changed to Department of Electrical Engineering and Computer Engineering. In 1995 it became the Department of Electrical and Computer Engineering.
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1909-present
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- Department of Electrical Engineering (1909-1985)
- Department of Electrical Engineering and Computer Engineering (1985-1995)
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- College of Engineering (parent college)
- Department of Physics and Electrical Engineering (predecessor)
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Abstract
We present a maximum likelihood (ML) method for semi-blind estimation of single-input multi-output (SIMO) flat-fading channels in spatially correlated noise having unknown covariance. An expectation-maximization (EM) algorithm is utilized to compute the ML estimates of the channel and spatial noise covariance. We derive the Crame´r-Rao bound (CRB) matrix for the unknown parameters and present a symbol detector that utilizes the EM channel estimates. Numerical simulations demonstrate the performance of the proposed method.
Comments
This is a post-print of an article from IEEE Transactions on Signal Processing 52 (2004): 1791–1797, doi:10.1109/TSP.2004.827200. Posted with permission.