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 />
BS,<br />
MS,<br />
σ φ<br />
σ ϕ<br />
10% 2.7 4.5 10.2 6.3<br />
50% 4.8 7.6 21.5 10.9<br />
90% 16.2 13.6 39.5 21.7<br />
mean 7.0 8.4 23.0 12.9<br />
10% 14.5 4.1 24.6 7.5<br />
50% 36.6 10.1 37.4 12.1<br />
90% 67.0 15.4 56.2 21.9<br />
mean 38.8 9.9 39.3 13.5<br />
(a) LOS (Corri-Corri)<br />
(b) NLOS (Corri.-Room)<br />
Figure 5.30: Example CDFs of Azimuth spreads at BS <strong>and</strong> MS.<br />
5.4.4.2 Scenario B1<br />
Figure 5.31 shows RMS azimuth angle-spread at the MS <strong>and</strong> for LOS <strong>and</strong> NLOS propagati<strong>on</strong> c<strong>on</strong>diti<strong>on</strong>s.<br />
Figure 5.32 presents RMS azimuth angle-spread at the BS for both LOS <strong>and</strong> NLOS propagati<strong>on</strong><br />
c<strong>on</strong>diti<strong>on</strong>s. We have not made any statistical fitting comparis<strong>on</strong> based <strong>on</strong> some well known techniques<br />
like KS test. However, based <strong>on</strong> Figure 5.31 the lognormal distributi<strong>on</strong> assumpti<strong>on</strong> is not as good as the<br />
log-logistic distributi<strong>on</strong> in fitting the RMS azimuth angle-spread at the MS for the case of LOS, while<br />
Gumbel distributi<strong>on</strong> has better fitting for the NLOS case. Distributi<strong>on</strong>s fitting to the RMS azimuth spread<br />
at the BS can be seen in Figure 5.32. Again for the LOS case, the log-logistic distributi<strong>on</strong> has better<br />
fitting to measurements than the lognormal distributi<strong>on</strong>. And again for NLOS case, the Gumbel<br />
distributi<strong>on</strong> has better fitting for the NLOS case.<br />
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