I am studying on a book (I'm still at basics) and I haven't understood why a signal with a lower number of harmonics implies a low bit rate. I have this figure:
It clearly shows how a signal with a high number of harmonics means that the bits are easier to "recognize". The bits in the last figure are 01100010. But it also shows the relationships between the number of harmonics and the bit rate:
My question is: shouldn't it be the opposite? A signal with many harmonics could represent more bits than a signal with few harmonics. A signal with N harmonics is able to carry N bits in a certain period of time T, while a signal with just one harmonic can carry just 1 bit in T nano seconds. But there is something wrong in my argument, could someone clarify this?
Best Answer
The table merely says that given a channel with a fixed bandwidth, if you transmit a signal through it (input can contain infinite harmonics), at the output only the first harmonics will get through, where a high baud rate (high fundamental frequency) will get less harmonics through than a low baud rate signal. In other words, a low baud rate signal will come out the other side relatively unaffected by the channel, while a high baud rate signal can be severely distorted (even completely filtered out).
This is important because if the signal gets too distorted, the original bits cannot be reliably recovered due to intersymbol interference and the increased relevance of noise perturbations.
So a low number of harmonics does not imply a low bit rate. Quite the opposite, a low bit rate implies a high number of harmonics going through the channel.
The general criterion for finding baud rate vs channel bandwidth limits are given by the Nyquist Criterion. Note that, although related, this is different than the sampling theorem mentioned in another answer (Shannon-Nyquist), because you are not trying to reconstruct an original "bandwidth limited signal" in the analog sense from a set of samples, it is a matter of determining the original symbols, which is related to threshold decisions, which can be based on sampling, transmitted power (areas), etc.