کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
563123 875472 2013 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A unified framework for regularized linear estimation in communication systems
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
پیش نمایش صفحه اول مقاله
A unified framework for regularized linear estimation in communication systems
چکیده انگلیسی

Two concerns often arise simultaneously when applying linear estimation in communication systems: the computational complexity can be prohibitively high when the system size is large, and the performance may degrade dramatically when the presumed model is mismatched with the actual system. In this paper, we introduce a subspace expansion framework to jointly address these concerns, in which the observation is first projected onto a lower-dimensional subspace and then the solution of the projected problem is regularized. We discuss two projection methods based on eigensubspace and Krylov subspace expansions. We show that the Krylov subspace projection provides an economical solution to regularized linear estimation. We also compare different regularization methods, such as principal components and diagonal loading. We show that diagonal loading generally outperforms other alternatives and that Krylov subspace rank reduction can yield a regularization effect close to diagonal loading. Finally, we investigate the impact of preconditioning on the performance and complexity for mismatched modeling and propose a loaded preconditioner, which can reduce complexity as well as preserve the regularization effect. Under the proposed framework, various regularization schemes are studied and some guidelines for choosing the right scheme are provided.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing - Volume 93, Issue 9, September 2013, Pages 2671–2686
نویسندگان
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