By Erik G. Larsson
This ebook is a self contained, good geared up and good awarded reference on MIMO conversation platforms. Authors have analyzed the topic in the matrix algebraic context. In exception of few typo errors(that have already been corrected via the authors) presentation of the topic is ideal and elementary to stick to. The unified framework for examining the topic offers the reader with a massive photograph of the topic. i like to recommend this ebook for anyone who desires to find out about the space-time coding.
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Additional info for Space-Time Block Coding for Wireless Communications
Sample text
N0 + L − 1; in the discussion we assume that Npost ≤ L. The samples n = 0, . . 6) l=0 where e(n) is a noise vector. Note that parts of the signal received during the preamble can in general depend on the data and the postamble in the previous burst. Also note that the received samples during the preamble and postamble, which do not depend on the unknown data, can be used for other tasks such as channel estimation. 3) as follows. Let ⎤ ⎡ H0 0 ··· 0 H L H L−1 · · · H 1 ⎢ .. ⎥ .. .. ⎢ 0 . .
Denote by {x(n)} for n = −Npre , . . , N0 + Npost − 1 the sequence of transmitted nt -vectors obtained by concatenating the preamble, the transmitted data corresponding to {s(n)}, and the postamble. Different choices of the mapping between {s(n)} and {x(n)} will be discussed later in the text, but in the special case of one transmit antenna (nt = 1), x(n) becomes a scalar x(n) and in that case no transmit encoding is necessary so we can simply set x(n) = s(n). The received signal is well-defined for n = L − Npre , .
8). 13), the latter formulation will be more useful for performance analysis. 3 The Time-Invariant Linear MIMO Channel Chapter 2 Summary and Discussion In this chapter we have introduced a unified matrix-algebraic framework for the MIMO propagation channel. 1). 2). Finally, we found that the input-output relation associated with both frequency flat and frequencyselective channels can be cast in the form y = (X T ⊗ I)h + e where y is a vector of received data, h is a vector of the channel, X is a (structured) matrix containing transmitted data and e is noise.