The noise that I am using is an impulsive noise which distribution is complex but can be approximated to a Middleton Class A distribution or an Alpha stable distribution. Those two distributions are well known but they are only approximations of my real noise.
I don't really know what is Capacity!
By definition it is the maximum number of bits per second that you can send over the channel with a very low probability of error.
So I was wondering if I make a very large number of Matlab simulations of transmitting symbols (BPSK modulated for example) from a transmitter to a receiver using a fixed Band width and a certain Signal to Interference Rate (SIR witch represents the power of the signal over the power of the noise), How can I measure the capacity of my channel ?
My idea is that I can calculate the Bit Error Rate (the number of error bits over the total number of bits). I will fix a minimum acceptable probability of error (say BER=10^-6).
Then I will calculate the number of correct received bits below my acceptable probability of error to find my channel capacity of that simulation.
After many simulations I will take the mean of all my calculated capacity witch will represent my channel capacity for a certain modulation, band width and SIR.
In other word I want to know how to calculate the channel capacity without using the mathematical formula.
PS: maybe I can use Shannon limit only as the theoretical limit for the maximum capacity.