Calculating Noise Power, SNR, and Bit Error Probability

In summary, the conversation discusses determining noise power, signal-to-noise ratio, and bit error probability based on time and voltage values. The use of noise figure is suggested as a method and formulas for calculating power and signal-to-noise ratio are mentioned. However, the calculation of noise power is dependent on the noise source and more information is needed to accurately determine the signal-to-noise ratio. The conversation ends with a formula for calculating bit error probability.
  • #1
viperfx
5
0
I have values of time, and volts of a noise signal.

I am trying to determine the noise power, signal to power ratio and bit error probability.

How would I go about doing this?

Thanks.
 
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  • #2
You start out with average power if you have the time and voltage.

Usually people use noise figure:

http://en.wikipedia.org/wiki/Noise_figure

Is that what you want? If so and you still have question, come back.
 
  • #3
Ah ok, thank you.

Is this the method for volt and time values obtained from scope? Currently I have the data in excel. I will read into noise figure.

If you have any particular formulas that could give me a start that would be great.
 
  • #4
As power is average, you need to take the average of the volt to the resistance or if you know the current you can calculate as

[tex]P= I_{RMS}V_{RMS}=\frac {V_{RMS}^2} R [/tex]

You have to use your data to find the RMS. Someone might want to come in about [itex]\frac 1 2[/itex]. I just don't remember when to put the half in or not.

You calculate the power of the signal, This is the easy part. The trick is knowing your noise source. You need to give a lot more information about the noise before you can get the signal to noise ratio. If it is electronic component noise, then you need to give your circuit and calculate from there.
 
  • #5
Yea I have come across many formulas like this, however the problem is I have values for only the time, and volts.
 
  • #6
Never mind. The Noise power is the variance (S.D. ^2), and the SNR is the Signal Power/Noise Power. Signal Power is A^2/2.
PE = 0.5erfc(V/2*variance*sqrt(2))

Thanks anyways.
 

1. What is noise power and why is it important?

Noise power is the amount of power present in a signal that is not relevant to the information being transmitted. It is important because it can influence the accuracy and quality of the signal, and therefore impact the overall performance of a system.

2. How is noise power calculated?

Noise power can be calculated by taking the power of the noise signal, which is usually measured in decibels (dB), and subtracting it from the total power of the signal and noise. The resulting value is the noise power.

3. What factors can affect noise power calculations?

The main factors that can affect noise power calculations include the type of noise present, the bandwidth of the signal, and the sensitivity of the measurement equipment. Additionally, external factors such as temperature and interference can also impact noise power.

4. How is noise power used in practical applications?

In practical applications, noise power calculations are used to determine the signal-to-noise ratio (SNR) of a system. This is important in areas such as telecommunications, where a high SNR is necessary for clear and accurate communication.

5. Can noise power be reduced or eliminated?

Noise power cannot be completely eliminated, but it can be reduced through various techniques such as filtering, shielding, and using low-noise components. However, reducing noise power too much can also decrease the overall signal power, so it is important to find a balance for optimal performance.

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