Aliasing
It is a phenomenon that occurs when a high-frequency signal is represented at lower frequency. Means it occurs when the sampling rate is insufficient and fails to capture the signal properly. When the signals are sampled at lower frequency than the nyquist frequency, high frequency components fold back (gets aliased) in the low frequency range. This may lead to distorted signal representation.
In simple words a high frequency component of a signal taking the identity of low frequency component of a signal when it is undersampled.
Methods to Avoid Aliasing
It can be avoided by the following two methods :
- Sampling at Nyquist Rate
- Using Anti-Aliasing Filter (Low Pass Filter): It helps removing the component above the nyquist frequency which may lead to aliasing.
Sampling in Digital Communication
Sampling in digital communication is converting a continuous-time signal into a discrete-time signal. It can also be defined as the process of measuring the discrete instantaneous values of a continuous-time signal.
Digital signals are easier to store and have a higher chance of repressing noise. This makes sampling an important step in converting analog signals to digital signals with its primary purpose as representing analog signals in a discrete format.
- Sampling Process in Digital Communication
- Nyquist – Shannon Sampling Theorem
- Oversampling & Undersampling
- Aliasing
- Why Sampling is Required?
- Methods of Sampling
- Scope of Fourier Transform
- Solved Examples on Sampling