Pulse Code Modulation(PCM)

The concise explanation for each of the subtopics in Pulse Code Modulation (PCM):

**Analog-to-Digital Conversion:**

The process of transforming continuous analog signals into discrete digital values is known as analog-to-digital conversion (ADC). The analog signal is sampled at regular intervals to collect its amplitude in this procedure. These samples are then quantized, which means that specific digital values from a finite set are assigned to them. ADC is essential for digital communication because it allows analog information to be transmitted and processed using digital systems.

**Quantization and Encoding:**

The process of converting a continuous range of analog signal amplitudes to a finite number of discrete levels in the digital realm is known as quantization. The disparity between the original analog value and the quantized digital representation is introduced as a result of this. Encoding entails utilizing a predetermined amount of bits to represent each quantized level. To reduce quantization noise and increase the overall quality of the digital signal, various quantization approaches, such as uniform and non-uniform quantization, as well as companding techniques, are used.

**Sampling Theorem and Nyquist Criterion:**

According to the Nyquist-Shannon Sampling Theorem, the sampling rate must be at least twice the highest frequency component present in the signal in order to accurately reconstruct a continuous signal from its samples. This eliminates aliasing, a phenomenon in which high-frequency components fold back into the baseband and distort the reconstructed signal. In digital communication, the Nyquist criteria assures that there is no overlap between subsequent symbols, eliminating inter symbol interference (ISI) and allowing for reliable signal identification.

These ideas are essential for comprehending how analog signals are efficiently converted to digital form, ensuring correct signal representation and transmission in digital communication systems.