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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 />

3.2.C<br />

Ricean with the corresp<strong>on</strong>ding K factor.<br />

Narrowb<strong>and</strong> phase angle distributi<strong>on</strong> of<br />

<strong>channel</strong> coefficients. Sum the <strong>channel</strong><br />

taps over delay domain for each time<br />

instant <strong>and</strong> each element of the MIMO<br />

matrix. The distributi<strong>on</strong> of the phase of<br />

each MIMO matrix element should be<br />

approximately uniform over (0,2*pi].<br />

Uniform pdf over<br />

(0,2*pi]<br />

7.1.3.3 Stochastic behaviour of the large-scale parameters<br />

Test id Test descripti<strong>on</strong> Expected outcome Notes<br />

3.3.A<br />

3.3.B<br />

3.3.C<br />

Bulk parameter statistics. Repeat all<br />

the results in Appendix 4.<br />

Path-loss <strong>models</strong> for all the scenarios<br />

except B1 NLOS. Repeat results in<br />

[D5.3, Sec. 2.3.1.13]. Calculate pathloss<br />

exp<strong>on</strong>ent <strong>and</strong> intercept <strong>and</strong><br />

compare to given values.<br />

Path-loss model for B1 NLOS. Fit a<br />

plane to resulting<br />

triplets.<br />

( log10<br />

d<br />

1,log10<br />

d<br />

2,<br />

PL)<br />

Compare the coefficients of plane<br />

equati<strong>on</strong> to values based <strong>on</strong> [D5.3, eq.<br />

2.6].<br />

The obtained results<br />

are very close to the<br />

‘input’ values.<br />

The obtained results<br />

are very close to<br />

[D5.3, sec. 2.3.1.13].<br />

Coefficients should<br />

be close to:<br />

a = 20.1<br />

b = 35.97<br />

c = 9.55<br />

Testing of mu, epsil<strong>on</strong>, <strong>and</strong> r<br />

values may be easier to do<br />

“within” the code (after step<br />

3) than from the output<br />

AoDs/AoAs. Note that, for<br />

example,<br />

E[log10(sigma_AS)]=mu_AS<br />

<strong>and</strong> STD(log10(sigma_AS))<br />

= epsil<strong>on</strong>_AS.<br />

The general equati<strong>on</strong> of<br />

plane:<br />

z = a*x + b*y + c<br />

7.1.3.4 Stochastic behaviour of CDL <strong>models</strong> output<br />

Test id Test descripti<strong>on</strong> Expected outcome Notes<br />

3.4.A<br />

3.4.B<br />

Estimate power delay profile from output<br />

<strong>channel</strong> matrices. Compare it to the <strong>on</strong>es<br />

given in [D5.3, Tables 4.7-16].<br />

Estimate amplitude probability density<br />

functi<strong>on</strong>s for <strong>models</strong>/clusters with LOS<br />

comp<strong>on</strong>ent. Compare distributi<strong>on</strong>s to<br />

Ricean distributi<strong>on</strong>s with desired K-<br />

factor.<br />

Resulting PDPs should<br />

match to <strong>on</strong>es given in<br />

[D5.3, Tables 4.7-16].<br />

Estimated PDFs<br />

should match<br />

theoretical <strong>on</strong>es.<br />

CDL <strong>models</strong> are<br />

selected by setting<br />

fixed PDP <strong>and</strong> Angles<br />

<strong>on</strong>.<br />

Theoretical PDFs must<br />

be generated by the<br />

test pers<strong>on</strong>.<br />

Page 147 (167)

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