"WINNER II Channel Models", ver 1.1, Sept

WINNER II D1.1.2 V1.1
Let us assume we have M LSPs per link and K correlated links, i.e. K MSs linked to the same BS site at
locations (x k ,y k ), where k = 1,…,K. Auto-correlation is generated to the LSPs the following way. At first
we generate a uniform grid of locations based on co-ordinates of the K MSs. Size of the grid is
( max( xk ) − min( xk
) + 2D) x ( max( yk
) − min( yk
) + 2D)
. To each grid node we assign M Gaussian iid
~N(0,1) random numbers, one for each LSP. Then the grid of random numbers is filtered with a two
dimensional FIR filter to generate exponential auto-correlation. Impulse response of the filter for the mth
LSP is
⎛ d
( ) ⎟ ⎞
h ⎜
m
d = exp − , (3.12)
⎝ ∆
m ⎠
where d is distance and ∆ m is the correlation distance both in meters (see Table 4-5). Each of the M
random numbers in nodes of the grid, representing M LSPs, is filtered with a specific filter, because the
correlation distances may be different in Table 4-5. After filtering the correlated random numbers
ξ x , y ) at K grid nodes (K MS locations) are saved and the redundant grid nodes are discarded.
M
(
k k
Cross-correlation is generated independently to the LSPs of K links by linear transformation
where elements of correlation matrix
are defined in Table 4-5.
~
s ( x , y ) = C (0) ξ ( x , y ) , (3.13)
k
k
MxM
M
k
⎡ C~ ⎤
s ~ (0)
~ ~ (0)
1s
L C
1
s1sM
⎢
⎥
C
MxM
(0) = ⎢ M O M ⎥
(3.14)
⎢ ~ ~
⎥
⎣
Cs
(0)
~ ~ (0)
M s
L C
1
sM
sM
⎦
k
3.4 Concept of channel segments, drops and time evolution
Channel segment represents a period of quasi-stationarity during which probability distributions of lowlevel
parameters are not changed noticeably. During this period all large-scale parameters, as well as
velocity and direction-of-travel for mobile station (MS), are practically constant. To be physically
feasible, the channel segment must be relatively confined in distance. The size depends on the
environment, but it can be at maximum few meters. Correlation distances of different parameters describe
roughly the proper size of the channel segment, see the paragraph 4.4.
Allowing the channel segment length go to zero, we specify a drop: In a drop all parameters are fixed,
except the phases of the rays. Motion within a drop is only virtual and causes fast fading and the Doppler
effect by superposition of rotating phasors, rays. It can be said, that a drop is an abstract representation of
a channel segment, where the inaccuracies caused by the change of the terminal location have been
removed. In a simulation, the duration of a drop can be selected as desired. It is a common practice to use
drops in the simulations. The main advantage is the simplicity of the simulation, because successive
simulation runs do not need to be correlated. The drawback is that it is not possible to simulate cases,
where variable channel conditions are needed. However, the drop-based simulation is the main method of
simulations in WINNER projects I and II. In the final WINNER II Channel Models there is also an
alternative for the drop-based simulation, i.e. simulation with time evolution., where correlated drops are
used
In the WINNER II models the propagation parameters may vary over time between the channel segments.
In the multi segment modelling two options are available, either drops (stationary channel segments like
in WINNER I) or continuous channel evolution with smooth transitions between segments. There are two
approaches for time evolution modelling discussed below. First is the one that is proposed to be
implemented, due to the simplicity of the method. Second is a method using Markov process that can be
regarded as a more advanced method and it requires parameters that have not been determined yet.
3.4.1 Basic method for time-evolution
In this report time evolution of propagation parameters is modelled like depicted in Figure 3-8. The route
to be modelled is covered by adjacent channel segments. The distance between segments is equal to the
stationarity interval. Transition from segment to segment is carried out by replacing clusters of the “old”
segment by the clusters of the “new” segment, one by one. The route between adjacent channel segments
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