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.

Learn about the sampling theorem in communication systems and its importance. Understand the implications of not sampling a signal according to the sampling theorem in communication systems.