How can we measure the BER if we assume a QAM signal is to be sent?

[ee_expert2000]

Hi,
Assuming that you send a Zero-Mean Gaussian signal through a channel which has White Non-Zero Mean Gaussian Noise but is Not Additive.
I say additive because the variance of the added noise is dependent on the input signal variance.
How can we measure the BER is we assume a QAM signal to be sent?
You can not use the formulas in the books.
They assume AWGN.
Any Hints or References!!!????
Thanks

 

[gied]

ber calculations

Hi,

I am little bit confused with your question, but in case your noise is signal dependent, then you can split it in two parts:
1. the part that is directly dependant on your input signal. Let's denote it as D. You can model this part like a multipath component in wireless communications.
2. AWGN = your whole noise signal - D.

Hope this helps

 

[ee_expert2000]

ber calculation

Hi,
How do you separate these two types of noise?
What part of my words is confusing you?
BR

 

[bulx]

matlab ber calculation

Why do you say it is not additive? It is still additive, its only that the noise power is (say) proportional to signal power. ie; noise in gaussian, but not stationary.

Standard approach to BER calcualtion is to find the conditional probability of error given the signal, when when signal has noise added to it. It would then become the tail probability of a gaussian function.

I think that can still be apllied: model the recieved signal as
r = s + n + n0 (if there is no n0, then noise can go to zero, if there is no signal)
n is a zero-mean signal-independent GRV whose variance is k times that of s.

question is what is prob (r > some_threshold |s) .
Guess this is the same as prob (n + n0 > some_threshold |s).
Assume signal(s) and n0 are independent.

So you would end up still with the same BER as in any standard scheme (like QAM). In way it is not surprising because, if we look at your problem from another angle, we are assuming that signal improves when noise increases. Does it make sense?
-b

 

[manojshukla]

ber calculation matlab

Your question is not clear.

 

[samuraign]

calculation of ber

I am not sure whether I understood ur prob clearly.

But as per my understanding u want to calculaye BER.
If ur system has QAM(Mapping)+CHANNEL-Model+QAM(De-Mapping),
then u just take the QAM-Mapper input and QAM-DeMapper output and calculate BER.
BER is the ratio of corrupted bits to total number of bits u sent.
If ur BER is good then u had a good DeMapper.

 

[ee_expert2000]

ber in matlab equation

This link is a good example on BER calculation by MATLAB.
**broken link removed**
I Hope it helps

 

[amihomo]

the calculate of ber

matlab has developed a BER calculation tool wich can be accessed by typing the following command in the matlab command prompt :


>>bertool

 

[muqarrab]

ber formula in 16 qam

you canf ind that in lathi

 

[mg777]

how to calculate ber calculation

The situation you describe holds for other situations as well e.g; Poisson. Provided you can invoke the Central Limit Theorem you can arm wave your way through a Gaussian approximation.

So, the bottom line is you'll do well to compare a Gaussian approximation with simulation or measurement results. Only for significant disparity would you worry about the raw BER anyway.

M.G.Rajan
www.eecalc.com