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14 - Blind and semiblind MIMO channel estimation

Published online by Cambridge University Press:  25 February 2010

Dirk Slock
Affiliation:
Institut Eurécom
Abdelkader Medles
Affiliation:
Bell Laboratories, Lucent Technologies
H. Bölcskei
Affiliation:
ETH Zürich, Switzerland
D. Gesbert
Affiliation:
Eurecom Institute
C. B. Papadias
Affiliation:
Bell Labs, Lucent Technologies
A.-J. van der Veen
Affiliation:
Technische Universiteit Delft, The Netherlands
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Summary

The goal of this chapter is to expose a number of key ideas in blind and, especially, semiblind (SB) channel estimation (CE), and attract attention to various considerations that should be kept in mind in this context. As will become clear, the topic considered is vast. Due to space limitations, the inclusion and discussion of references is far from exhaustive. See also de Carvalho and Slock (2001) for an overview of semiblind single-input multiple-output (SIMO) channel estimation approaches. The use of blind information in digital communications is motivated by a desire to limit capacity loss due to training. Such capacity loss potentially increases with increasing time variation, occupied bandwidth, and number of transmitters. In other applications, blind techniques may be the only option (e.g., acoustic dereverberation). A particularity of digital communications, however, is that the sources are discrete time, white, and finite alphabet.

Signal model

In a first instance, the nonblind information considered will be provided by training or pilot information. As for terminology, the term training sequence (TS) tends to be used for a limited consecutive sequence of known symbols, whereas pilot symbols are typically isolated known symbols. A pilot signal is a continuous stream of known symbols, superimposed on the data signal.

Type
Chapter
Information
Space-Time Wireless Systems
From Array Processing to MIMO Communications
, pp. 279 - 301
Publisher: Cambridge University Press
Print publication year: 2006

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