Adaptive Algorithms for Sparse Nonlinear Channel Estimation

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Adaptive Algorithms for Sparse Nonlinear Channel Estimation

Show simple item record Tarokh, Vahid Babadi, Behtash Mileounis, Gerasimos Kalouptsidis, Nicholas 2010-10-14T14:14:36Z 2009
dc.identifier.citation Kalouptsidis, Nicholas, Gerasimos Mileounis, Behtash Babadi, and Vahid Tarokh. 2009. Adaptive algorithms for sparse nonlinear channel estimation. Paper presented at the 2009 IEEE Workshop on Statistical Signal Processing, Cardiff, Wales, UK. en
dc.description.abstract In this paper, we consider the estimation of sparse nonlinear communication channels. Transmission over the channels is represented by sparse Volterra models that incorporate the effect of Power Amplifiers. Channel estimation is performed by compressive sensing methods. Efficient algorithms are proposed based on Kalman filtering and Expectation Maximization. Simulation studies confirm that the proposed algorithms achieve significant performance gains in comparison to the conventional non-sparse methods. en
dc.description.sponsorship Engineering and Applied Sciences en
dc.language.iso en_US en
dash.license OAP
dc.title Adaptive Algorithms for Sparse Nonlinear Channel Estimation en Tarokh, Vahid 2010-10-14T14:14:36Z

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