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What is the significance of Shannon capacity over Nyquist bit rate?
The Shannon formula gives us 6 Mbps, the upper limit. For better performance we choose something lower, 4 Mbps, for example. Then we use the Nyquist formula to find the number of signal levels. The Shannon capacity gives us the upper limit; the Nyquist formula tells us how many signal levels we need.
Why do we use Shannon and Nyquist theorem?
The Nyquist–Shannon sampling theorem is a theorem in the field of signal processing which serves as a fundamental bridge between continuous-time signals and discrete-time signals. The theorem also leads to a formula for perfectly reconstructing the original continuous-time function from the samples.
How does the Nyquist formula relate data rate and bandwidth?
Background The Nyquist formula gives the upper bound for the data rate of a transmission system by calculating the bit rate directly from the number of signal levels and the bandwidth of the system. Specifically, in a noise-free channel, Nyquist tells us that we can transmit data at a rate of up to C = 2B log2 M C = 2 B l o g 2 M
Why does Shannon get the theorem and Nyquist the rate?
I don’t think that anyone is trying to separate Nyquist from his rate, so we end up with a good compromise: Shannon gets the theorem, and Nyquist gets the rate. If we apply the sampling theorem to a sinusoid of frequency f SIGNAL, we must sample the waveform at f SAMPLE ≥ 2f SIGNAL if we want to enable perfect reconstruction.
How to calculate the maximum data rate for a noisy channel?
used, to determine the theoretical highest data rate for a noisy channel: Capacity = bandwidth * log 2 (1 + SNR) In the above equation, bandwidth is the bandwidth of the channel, SNR is the signal-to-noise ratio, and capacity is the capacity of the channel in bits per second.
Which is the upper bound of the Nyquist formula?
The Nyquist formula gives the upper bound for the data rate of a transmission system by calculating the bit rate directly from the number of signal levels and the bandwidth of the system. Specifically, in a noise-free channel, Nyquist tells us that we can transmit data at a rate of up to C = 2B log2 M C = 2 B l o g 2 M