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WINNER II pdf - Final Report - Cept

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<strong>WINNER</strong> <strong>II</strong> D1.1.2 V1.2<br />

( τ ' − min( τ '))<br />

τ = sort<br />

. (4.2)<br />

n<br />

n<br />

In the case of LOS condition additional scaling of delays is required to compensate the effect of LOS<br />

peak addition to the delay spread. Heuristically determined Ricean K-factor dependent scaling<br />

constant is<br />

D +<br />

n<br />

2<br />

3<br />

= 0.7705−<br />

0.0433K<br />

+ 0.0002K<br />

0.000017K<br />

, (4.3)<br />

where K [dB] is the Ricean K-factor defined in Table 4-5. Scaled delays are<br />

LOS<br />

τ = τ D , (4.4)<br />

n n<br />

/<br />

they are not to be used in cluster power generation.<br />

Step 6: Generate the cluster powers P.<br />

The cluster powers are calculated assuming a single slope exponential power delay profile. Power<br />

assignment depends on the delay distribution defined in Table 4-5. With exponential delay distribution<br />

the cluster powers are determined by<br />

'<br />

⎛<br />

Pn<br />

= exp<br />

⎜−<br />

⎝<br />

n<br />

r 1⎞<br />

τ<br />

−<br />

10<br />

r<br />

⎟ ⋅<br />

τστ<br />

⎠<br />

and with uniform delay distribution they are determined by<br />

'<br />

P n<br />

−Ζ<br />

10<br />

n<br />

τ (4.5)<br />

⎛ −τ<br />

⎞<br />

n<br />

= exp<br />

⎜<br />

⎟ ⋅ 10<br />

⎝ σ τ ⎠<br />

−Ζ<br />

10<br />

n<br />

, (4.6)<br />

where Ζ n ~ N(0, ζ ) is the per cluster shadowing term in [dB]. Average the power so that sum power of<br />

all clusters is equal to one<br />

P<br />

'<br />

n<br />

n<br />

=<br />

N<br />

∑ n = 1<br />

P<br />

Assign the power of each ray within a cluster as P n / M, where M is the number of rays per cluster.<br />

Step 7: Generate the azimuth arrival angles ϕ and azimuth departure angles φ.<br />

If the composite PAS of all clusters is modelled as wrapped Gaussian (see Table 4-5) the AoA are<br />

determined by applying inverse Gaussian function with input parameters P n and RMS angle spread σ ϕ<br />

On equation above 1. 4<br />

AoA<br />

2 ln<br />

' = σ AoA<br />

−<br />

C<br />

P<br />

'<br />

n<br />

( P max( P ))<br />

(4.7)<br />

n<br />

n<br />

ϕ<br />

n<br />

. (4.8)<br />

σ = σ is the standard deviation of arrival angles (factor 1.4 is the ratio<br />

ϕ<br />

of Gaussian std and corresponding ”RMS spread”). Constant C is a scaling factor related to total<br />

number of clusters and is given in the table below:<br />

# clusters 4 5 8 10 11 12 14 15 16 20<br />

C 0.779 0.860 1.018 1.090 1.123 1.146 1.190 1.211 1.226 1.289<br />

In the LOS case constant C is dependent also on Ricean K-factor. Constant C in eq. (4.10) is<br />

substituted by C LOS . Additional scaling of angles is required to compensate the effect of LOS peak<br />

addition to the angle spread. Heuristically determined Ricean K-factor dependent scaling constant is<br />

2<br />

3<br />

( 1.1035<br />

− 0.028K<br />

− 0.002K<br />

0.0001K<br />

)<br />

C LOS C ⋅<br />

+<br />

= , (4.9)<br />

where K [dB] is the Ricean K-factor defined in Table 4-5.<br />

Assign a positive or negative sign to the angles by multiplying with a random variable X n with<br />

uniform distribution to discrete set of {1,–1}, add component N( 0, 5)<br />

random variation<br />

n<br />

n<br />

n<br />

n<br />

LOS<br />

n<br />

~<br />

AoA<br />

Y σ to introduce<br />

ϕ = X ϕ ' + Y + ϕ , (4.10)<br />

where ϕ LOS is the LOS direction defined in the network layout description Step1.c.<br />

Page 39 (82)

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