Digital Signal Processing Reference
In-Depth Information
25
20
15
MIMO
10
SIMO
5
MISO
0
1
2
3
4
5
6
7
8
9
10
M
FIgure 4.4
Capacity for MIMO, SIMO, and MISO structures; uncorrelated Rayleigh flat fad-
ing; SNR = 10 dB,
P
out
= 0.01.
the line of sight (LOS) to the total received average power [41]. For relatively high RF that
can be regarded as a more correlated channel, the WF gain is quite considerable.
4.4
Iterative Signal Detection
Signal detection is a crucial part of the transmission system. Among the various detec-
tion techniques proposed for the case of MIMO systems, there are iterative (also called
turbo
) detectors. This is what we are going to focus on in this section. In effect, since the
invention of turbo-codes by Berrou and Glavieux [42], who proposed iterative decoding
of parallel concatenated convolutional codes, the
turbo principle
has been applied to
several problems in communications, such as channel equalization [43], channel esti-
mation [44], synchronization [45], multiuser detection [46, 47], and, of course, MIMO
signal detection [48]. The turbo principle consists of the exchange of
sot
information
between two different stages of the Rx, mostly including the soft channel decoder. In
MIMO systems too, iterative processing has attracted special attention as it makes a
good compromise between complexity and performance. Before presenting the basics
of iterative detection, we have to present a brief introduction on space-time coding that
is performed at the Tx. We mostly consider frequency-non-selective (flat) fading condi-
tions and single-carrier modulation.
4.4.1 Space-Time Coding and Decoding
An important aspect in the implementation of MIMO systems is to appropriately
distribute redundancy in space and in time at the Tx, what is called space-time (ST)
coding [49]. To date, there has been considerable work on this subject, and a variety
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