Problem with Minimum Nyquist bandwidth formula and m-ary encoding

In summary, the book Electronic Communication Systems by Wayne Tomasi discusses the minimum theoretical bandwidth necessary for signal propagation, known as the minimum Nyquist bandwidth or minimum Nyquist frequency. The book provides two formulas for this bandwidth, fb=2B and fb=2Blog2M, the latter being used for multilevel signaling. However, there is confusion about the presence of the number 2 in the second formula, with the author possibly making a mistake in differentiating between sampling frequency and Nyquist frequency. It is recommended to consult with the lecturer about this error.
  • #1
iampaul
93
0
I am using the book Electronic Communication Systems by Wayne Tomasi:
I had a problem with a certain part of the book:
The book gives the formula for the minimum nyquist bandwidth as:

" The minimum theoretical bandwidth necessary to propagate a signal is called the minimum Nyquist bandwidth or sometimes the minimum nyquist frequency. Thus, fb=2B, where fb is the bit rate in bps and B is the ideal nyquist bandwidth."

Then it says that:
"Using multilevel signaling, the nyquist formultion for channel capacity is fb=2Blog2M. This equation can be rearranged to solve for the minimum bandwidth necessary to pass M-ary digitally modulated carriers. B=fb/log2M" ?

What happened to the number 2 in 2Blog2M?? I thought it was just a typo but then it used this equation for the next discussions.

Please reply, thanks in advance!
 
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  • #2
I looked around online documents on the topic and can find no support for dropping the 2. My money's on it being a textbook blunder. (But considering my meagre bank balance, that isn't saying much!)

Have you raised the matter with your lecturer?
 
  • #3
It seems to me the errror is that the 2's shouldn't be there.

The Nyquist bandwidth is half the sampling frequency. A sampled signal of 1, 0, 1, 0, ... is at the Nyquist frequency and requires 1 bit per sample, so I think the first equation should be bf = B.

log2M is the number of bits required to give M distinct sample levels. A single-bit signal needs 2 levels, not 1, and log22 = 1, so the 2 didn't appear or disappear because of that.

But even if the above comments are wrong, you certainly can't "lose" the 2 just by rearranging the equation fb=2Blog2M to get B=fb/log2M.

I guess the mistake(s) came from the author "knowing the right formula" but forgetting whether he/she was talking about the sampling frequency or the Nyquist frequency.
 

What is the Nyquist bandwidth formula?

The Nyquist bandwidth formula is a mathematical equation that relates the minimum bandwidth required for a signal to be transmitted without interference to the symbol rate of the signal. It is often used in digital communication systems to determine the maximum data rate that can be achieved without errors.

What is the problem with the minimum Nyquist bandwidth formula?

The problem with the minimum Nyquist bandwidth formula is that it assumes an ideal channel with no noise or interference. In reality, most communication channels have some level of noise and distortion, which can result in errors and reduce the data transmission rate.

How does m-ary encoding affect the minimum Nyquist bandwidth formula?

M-ary encoding is a technique used to increase the data transmission rate by encoding multiple bits of information into a single symbol. This can result in a higher data rate than what the Nyquist bandwidth formula predicts, as it does not take into account the use of encoding schemes.

Is the minimum Nyquist bandwidth formula still relevant in modern communication systems?

Yes, the minimum Nyquist bandwidth formula is still relevant in modern communication systems. However, it is often used in conjunction with other techniques, such as error-correcting codes and adaptive modulation, to achieve higher data rates and improve the overall performance of the system.

How can the problem with the minimum Nyquist bandwidth formula be addressed?

The problem with the minimum Nyquist bandwidth formula can be addressed by using advanced coding and modulation techniques, such as trellis coding, turbo coding, and quadrature amplitude modulation (QAM). These techniques can help to mitigate the effects of noise and interference and improve the data transmission rate.

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