Why Sampling is Required?
Sampling plays an essential role in digital communication systems because it turns continuous analog signals into discrete digital data, allowing them to be processed, transmitted, stored, and manipulated efficiently in the digital world. Noise reduction, error detection and correction, compression, signal processing, and interoperability are all enabled by this conversion, which is crucial for modern communication systems. Digital representation provides for long-distance data transmission with reduced signal deterioration, as well as precise modulation, demodulation, and other signal processing processes, facilitating dependable communication and compatibility among diverse devices and platforms.
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