Final report on link level and system level channel models - Winner
Final report on link level and system level channel models - Winner
Final report on link level and system level channel models - Winner
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WINNER D5.4 v. 1.4<br />
5.4.12.5 Scenario D1<br />
The CDF of the cross-polarizati<strong>on</strong> ratio (XPR) at 100 MHz b<strong>and</strong>width <strong>and</strong> 5.25 GHz centre-frequency in<br />
a rural envir<strong>on</strong>ment is shown in the Figure 5.69. The corresp<strong>on</strong>ding percentiles are listed in the Table<br />
5.44.<br />
Table 5.44: Percentiles of the cross-polarizati<strong>on</strong> ratios in a D1 rural envir<strong>on</strong>ment.<br />
D1 rural<br />
direct path<br />
(LOS)<br />
scattered paths<br />
(NLOS)<br />
10% 1.7 3.7<br />
XPR V 50% 12.2 6.3<br />
90% 20.7 9.2<br />
mean / std 11.7 / 7.8 6.4 / 2.2<br />
XPR H<br />
10% 3.2 3.2<br />
50% 13.5 6.1<br />
90% 23.3 9.1<br />
mean / std 13.2 6.1 / 2.3<br />
Figure 5.69: CDFs for the XPR V <strong>and</strong> XPR H for 5.25 GHz.<br />
5.4.13 Large-scale parameter analysis item<br />
In Secti<strong>on</strong> 3.1, the model for the so-called large-scale parameters are introduced. In the following<br />
subsecti<strong>on</strong>s the required parameters are estimated for scenario A1 LOS/NLOS, B1 LOS/NLOS, B3<br />
LOS/NOS, C1 LOS/NLOS, C2 NLOS <strong>and</strong> D1 LOS/NLOS. In all cases except A1, the vector of bulk<br />
parameters s( x, y)<br />
has four dimensi<strong>on</strong>s corresp<strong>on</strong>ding to the delay-spread, AoD spread, AoA spread <strong>and</strong><br />
log-normal shadowing. In A1, it has the additi<strong>on</strong>al dimensi<strong>on</strong> of AoD elevati<strong>on</strong> spread <strong>and</strong> AoA elevati<strong>on</strong><br />
spread. The required parameters are the vector of transformati<strong>on</strong> functi<strong>on</strong>s ~ s ( x , y)<br />
= g( s( x,<br />
y)<br />
), which<br />
s x, y into a vector ~ s ( x, y)<br />
of four Gaussian r<strong>and</strong>om variables. The mean<br />
transfoRMS the bulk vector ( )<br />
µ <strong>and</strong> correlati<strong>on</strong> R( 0)<br />
of the transformed r<strong>and</strong>om variable, <strong>and</strong> the decorrelati<strong>on</strong> distance parameters<br />
λ , K λ determine the variati<strong>on</strong> of the large-scale vector over the cell area through the equati<strong>on</strong>s<br />
1<br />
,<br />
4<br />
2<br />
E { ( x , y ) s( x y )} = R( ∆r)<br />
( ) ( ) 2<br />
R<br />
s<br />
1 1 2,<br />
2<br />
⎛<br />
⎜<br />
⎝<br />
⎛<br />
⎜<br />
⎝<br />
∆ r = x<br />
(5.27)<br />
2 − x1<br />
+ y2<br />
− y1<br />
∆r<br />
⎞ ⎛ ∆r<br />
⎞⎞<br />
⎟<br />
K<br />
⎜ ⎟⎟<br />
, (*) (5.28)<br />
λ1<br />
⎠ ⎝ λm<br />
⎠⎠<br />
0.5<br />
0.5,T<br />
( ∆r) = R ( 0) diag⎜exp⎜−<br />
⎟,<br />
,exp⎜−<br />
⎟⎟R<br />
( 0)<br />
0.5<br />
T 0.5<br />
5<br />
where R ( 0)<br />
is obtained from the eigendecompositi<strong>on</strong> R( 0) = EΛE<br />
as ( 0) = EΛ<br />
0.<br />
R .<br />
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