Sampling Theorem in Communication Systems

Sampling Theorem in Communication Systems

• The sampling theorem states that a continuous-time signal can be perfectly reconstructed from its samples if the sampling rate is greater than twice the highest frequency component of the signal.
• The minimum sampling rate required to avoid aliasing is known as the Nyquist rate, which is twice the bandwidth of the signal.

Consequences of Insufficient Sampling

• If a signal is not sampled according to the sampling theorem, it leads to aliasing, which causes distortion and loss of original information.
• Aliasing occurs when the sampling rate is less than the Nyquist rate, resulting in overlapping of frequency spectra.

Importance of the Sampling Theorem

• Abiding by the sampling theorem ensures that the original continuous-time signal can be perfectly reconstructed from its samples.
• Failure to follow the sampling theorem can result in loss of information, distortion, and inaccurate representation of the original signal.