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• W2017391623 abstract "In this paper, three MIMO robust equalization problems are considered for non-parametric classes of channel models defined by weighted H2 or H∞ balls (of frequency-responses) and performance criteria based on H2 (variance) or H∞ norms of error signals. The approach pursued here centers on characterizing the worst-case performance of candidate equalizers, or upper bounds on it, by means of dual Lagrangian functionals. Then, for linearly parametrized, finite-dimensional classes of candidate equalizers, the corresponding robust equalization problems are converted into semi-definite linear programming problems for which approximate solutions can be effectively computed. A simple numerical example is presented, involving H2 model uncertainty and error-variance performance, to illustrate, for various levels of uncertainty, the changes in the worst-case performances of the nominally optimal equalizer and of the one, in a specific linear class, which minimizes the worst-case error variance." @default.
• W2017391623 created "2016-06-24" @default.
• W2017391623 creator A5044568989 @default.
• W2017391623 date "2014-03-01" @default.
• W2017391623 modified "2023-09-25" @default.
• W2017391623 title "Robust MIMO Equalization for Non-Parametric Channel Model Uncertainty" @default.
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• W2017391623 doi "https://doi.org/10.1109/tsp.2014.2298378" @default.
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