Hi Raya,
As per my understanding, you would like to augment 3000 IQ packets via κ -μ / inverse gamma composite fading channel.
I would suggest you create a custom implementation to simulate this channel model. You could generate κ -μ and inverse gamma random variables using the 'gamrnd' function. Then, you could apply fading to the IQ packets by multiplying the IQ packets with the fading coefficients obtained from the κ -μ and inverse gamma distributions.
The following code may help you understand this:
% Parameters for κ-μ distribution
kappa = 2; % Shape parameter
mu_k = 1; % Mean parameter
% Parameters for inverse gamma distribution
alpha = 2; % Shape parameter
beta = 1; % Scale parameter
% Example IQ packets
original_packets = randn(1, 3000) + 1i * randn(1, 3000);
% Generate fading coefficients for κ-μ distribution
fading_kmu = sqrt(gamrnd(kappa, mu_k^2/kappa, 1, 3000));
% Generate fading coefficients for inverse gamma distribution
fading_inv_gamma = sqrt(1 ./ gamrnd(alpha, 1/beta, 1, 3000));
% Apply fading to IQ packets
augmented_packets = fading_kmu .* fading_inv_gamma .* original_packets
Kindly have a look at the following documentation links to have more information on:
- 'gamrnd' function : https://www.mathworks.com/help/stats/gamrnd.html
- 'randn' function: https://in.mathworks.com/help/matlab/ref/randn.html
Hope that helps!
Balavignesh
