channel response to user k and has the distribution:
gk ∼ CN(0, βk I), k = 1, 2, . . .,K,
n ∼ CN(0, I) is a noise
{which is a circularly symmetric complex Gaussian random vector.
The variance βk > 0 represents the large-scale fading including path loss and shadowing, and is normalized by the noise variance at the BS to simplify the notation.
The users are assumed to be uniformly and randomly distributed in a cell with radius R = 1000 m and not user closer than 100 m to the BS. The path-loss model is chosen as βk = zk /r3.76 k where
rk is the distance of user k from the BS where zk represents
the independent shadowing effect. Shadowing is chosen to be
log-normal distributed with a standard deviation of 8 dB.}
i cant understanding that term (and is normalized by the noise variance at the BS to simplify the notation)
my matlab code for generate βk:
for kk=1:K
sigma_shd=8; %in dB
L=0;
z(kk) = sigma_shd*randn(1,1);
%r(kk) is a distance between user kk and BS 100m
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