Daniel, P. Palomar, Yi Jiang's MIMO Transceiver Design via Majorization Theory (Foundations PDF

By Daniel, P. Palomar, Yi Jiang

Multiple-input multiple-output (MIMO) channels supply an summary and unified illustration of alternative actual conversation structures, starting from multi-antenna instant channels to instant electronic subscriber line (DSL) structures. they've got the most important estate that numerous information streams might be at the same time proven. MIMO Transceiver layout through Majorization idea provides an updated unified mathematical framework for the layout of point-to-point MIMO transceivers with channel kingdom info (CSI) at each side of the hyperlink in keeping with an arbitrary price functionality as a degree of the approach functionality. additionally, the framework embraces the layout of structures with given person functionality at the facts streams. MIMO Transceiver layout through Majorization concept is a useful source for researchers and practitioners excited by the cutting-edge layout of MIMO-based verbal exchange platforms.

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Extra resources for MIMO Transceiver Design via Majorization Theory (Foundations and Trends in Communications and Information Theory)

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In this chapter, we introduce the basic notion of majorization and state some basic results. 1 The 1997 book by Bhatia [15] contains significant material on majorization theory as well. , [66, Sec. 3]2 and [4, Sec. 10]. 1 Basic Definitions Majorization makes precise the vague notion that the components of a vector x are “less spread out” or “more nearly equal” than the components of a vector y. 1 Interestingly, a revised version of the book, co-authored by Marshall, Olkin, and Arnold, will be published soon by Springer-Verlag.

Yi−1 , α yi + (1 − α) yj , yi+1 , . . , yj−1 , α yj + (1 − α) yi , yj+1 , . . , yn ]T . 2 Basic Results We start with some fundamental majorization relations. 1. [97, p. 7] For any vector x ∈ Rn , let 1 ∈ Rn denote the n vector with equal elements given by 1i j=1 xj /n. Then 1 ≺ x. 1 is simply stating the obvious fact that a vector of equal components has the “least spread out” or the “most equal”components among all vectors. The following is a fundamental result on the application of majorization theory to matrices.

In an attempt to simplify these problems and in light of the optimality of the diagonal structure for transmission in all the previous examples (including the capacity-achieving solution [33, 122, 148]), one might expect that the same would hold for any other criteria as well. However, as shown in [111], this is not the case. In [106], the minimization of the BER (and also of the Chernoff upper bound) averaged over the channel substreams was treated in detail when a diagonal structure is imposed.

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