A question on Shannons Formula Simplification

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In summary, the Shannons Formula for finding the capacity of a channel is unreliable if the Signal Noise Ratio is high. The simplified formula gives the capacity as B * log(base 2) [10^(SNRdb/10)], where SNRdb is the dB of the signal noise ratio.
  • #1
dragonflare
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Hello all, i encountered a question which i coudnt really solve, was hoping someone could help me. Its regarding Shannons Formula for finding capacity of a channel.

So it goes like this:

C = B log (base2 ) [1 + SNR]

KEY:
C = capacity
B = bandwidth
SNR = SIgnal Noise Ratio

when the SNR (Signal Noise Ratio) is high, the above formula is not very reliable and we can use this formula instead:

*Also it states that if the SNR is high we can ignore the 1.

C = B * [SNR(subscript db)/3]

Question: How do we get the second formula after simplifying the first?-------------------------------------------------------------------------------------

This is what i have tried till now.

SNR(subscript db) = 10 log (base 10) SNR

We make SNR subject of formula :

10^(SNRdb/10) = SNR

Therefore substituting SNR in the text with the SNR (subscript dB)gives you

*We ignore the 1

C = B * log (base 2) [ 10 ^ (SNRdb / 10)]

Now I am given to understand that to find log base 2 of a number we can do this:C = [B * log (base 10) [ 10 ^ (SNRdb / 10)]] / [log (base 10) 2]

...

I am really confuse how to simplify after that.. i don't even know if I am right in the first place -.-

Any help would be appreciated.

Thanks

How do we go to this simplified formula from the one given above??
 
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  • #2
It looks like you basically have this, if not in a form you are recognizing: you use the "change-of-base" formula for logarithms to write

log(2) SNR = [ log(10) SNR ] / [ log(10) 2 ] .

Now from your formula 10^(SNRdb/10) = SNR , we have

SNRdb/10 = log(10) SNR .

Upon substituting this into the earlier equation, we get

log(2) SNR = [ SNRdb/10 ] / [ log(10) 2 ] = [ SNRdb ] / [ 10 log(10) 2 ]

The common log of 2 is 0.3010... , so 10 log(10) 2 is real close to 3 .

We can now put these pieces together to get, for SNR >> 1 ,

C = B log(2) [1 + SNR] ≈ B log(2) SNR ≈ B * [ SNRdb ] / 3 .
 
  • #3
thanks for the reply :) i better understand my mistake.. i forgot to make it into the value 0.3 ... silly me :|

thanks anyway :D
 

Related to A question on Shannons Formula Simplification

1. What is Shannon's Formula Simplification?

Shannon's Formula Simplification is a mathematical formula developed by the American mathematician Claude Shannon in 1948. It is used to determine the maximum rate of information that can be transmitted over a communication channel with a certain amount of noise present.

2. How is Shannon's Formula Simplification calculated?

The formula is calculated by multiplying the bandwidth of the channel (measured in Hertz) by the logarithm of the signal-to-noise ratio (measured in decibels) and then subtracting that value from the logarithm of the number of available signal levels. This results in the maximum number of bits per second that can be reliably transmitted over the channel.

3. What is the importance of Shannon's Formula Simplification?

Shannon's Formula Simplification is important because it provides a theoretical limit for the amount of information that can be transmitted over a communication channel. This has been instrumental in the development of modern communication systems and has helped engineers and scientists to optimize the efficiency and reliability of data transmission.

4. Are there any limitations to Shannon's Formula Simplification?

Yes, there are some limitations to the formula. It assumes that the noise present in the channel is independent of the transmitted signal and that the channel has a constant bandwidth. In real-world scenarios, these assumptions may not always hold true, which can affect the accuracy of the formula's predictions.

5. How is Shannon's Formula Simplification used in practical applications?

Shannon's Formula Simplification is used in various practical applications, such as telecommunications, wireless communications, data storage, and digital signal processing. It is used to determine the maximum data rate for a given channel and to optimize the design of communication systems to achieve the highest possible data transfer rate while minimizing errors.

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