Digital Signal Processing Reference
In-Depth Information
The uncorrelated scattering assumption leads to a finite impulse response
(FIR) channel model in which all the taps vary independently. That is, the time
variations of the tap coefficients are mutually uncorrelated while exhibiting
the same time-correlation behavior. The physical situation underlying this
model is the existence of a few large scatterers far from the mobile receiver
and the existence of a small number of scatterers in the vicinity of the mobile
receiver. Classical analysis of digital transmission through a fading medium
models
h
ij
(
as zero-mean random variables. In certain applications, such
as cellular communications, a direct nonfading path may also exist, superim-
posed on the fading path. In this case, the coefficients
h
ij
(
t,
τ)
have nonzero
mean (Rician fading). The overall nonzero mean channel is then:
17
,
18
t,
τ)
h
ij
(
h
ij
(τ )
+
t,
τ)
=
h
ij
(
t,
τ)
,
(8.2)
h
ij
(τ )
where
0.
As pointed out in Reference 19, accurate mathematical channel models are
based on collected measurements of actual channels. The channel models that
are employed in GSM system are defined in Reference 11. Measurements have
been made over typical bandwidths of 10 to 20 MHz at or near 900 MHz. Four
propagation environments are described in the project: Typical Urban (TU),
Bad Urban (BU), Hilly Terrain (HT), and Rural Area (RA), each of which has
specific parameter sets including delay and power profiles. These propaga-
tion environments are determined by individual delay distributions that are
piecewise exponential functions.
More advanced channel models taking into account the spatial compo-
nent are being developed. Models for WCDMA and multicarrier systems
have been derived and validated by measurements. Classical channel mod-
els provide information on signal power level distribution and Doppler shifts
of received signals. Modern spatial channel models incorporate concepts as
time delay spread, angles of arrival and departure, and different antenna
geometries.
20
,
21
An overview of spatial channel models is presented in
Reference 22. Much research and many measurements of channel models
have been done at AT&T Laboratories.
23
Several other models are presented
in special publications on channel modeling, such as Reference 15.
is a constant mean and
E
[
h
ij
(
t,
τ)
]
=
8.2.1
MIMO Channel Modeling
In the MIMO scenario we have a channel matrix
H
, which models the medium
between the
m
transmit and
n
receive antennas. Typically, the channels are
considered to be independent. This assumption holds if the spacing between
the antenna elements is larger than the coherence distance. Real environment
measurement campaigns are ongoing in order to derive better models for
MIMO channels. Key concepts such as antenna spacing, antenna height, scat-
tering radius at both mobile and base station, and the placement of these
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