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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 />

Page 105 (167)

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