# Quantizer | Quantization in digital communication

In this lecture, we will learn about Quantization, How quantizer works, and the types of Quantization process in a very detailed manner. So let’s discuss each topic one by one. So first we will start with the concept of Quantization.

## Concept of Quantization

• In a communication system, sometimes happen that we are available with an analog signal, however, we have to transmit a digital signal for a particular application. In such a case, we have to convert an analog signal into a digital signal. This means that we have to convert a continuous-time signal into the form of digits.
• To see how a signal can be converted from analog o digital form, let us consider an analog signal as shown in figure (a). First of all, we get samples of this signal according to the sampling theorem. For this purpose, we mark the time instants t0, t1, t2, and so on, at equal time intervals along the time axis. At each of these time instants, the magnitude of the signal is measured and thus samples of the signal are taken. Figure (b) shows a representation of the signal of figure a in terms of samples.
• Now, we can say that the signal in figure (b) is defined only at the sampling instants. This means that it no longer is continuous function time, but rather, it is a discrete-time signal. However, since the magnitude of each sample can take any value in a continuous range, the signal in figure(b) is still an analog signal.
• Ths difficulty is nearly resolved by a process known as quantization. In quantization, the total amplitude range that the signal may occupy is divided into a number of standard levels.
• As shown in figure (c), the amplitude of the signal x(t) lies in the range (-mp, mp) which is partitioned into L intervals, each of magnitude \Delta v=\frac{2m_p}{L}. Now each sample is approximated or rounded off to the nearest quantized level as shown in the figure.

## Quantizer

• As discussed earlier, a q-level quantizer compares the discrete-time input x(nTs) with its fixed digital levels. It assigns any one the digital level to x(nTs) with its fixed digital levels. It then assigns any one of the digital levels to x(nTs) which results in minimum distortion or error. This error is called quantization error. Thus the output of a quantizer is a digital level called xq(nTs).

## Types of Quantization

Basically, the quantization process may be classified as follows:

The quantization process can be classified into two types:

(i) Uniform Quantization

(ii) Non-uniform Quantization

1. Uniform Quantizer: A uniform quantizer is that type of quantizer in which the step size remains the same through the input range.

2. Non-uniform Quantizer: A non-uniform quantizer is that type of quantizer in which the step size varies according to the input signal values.

### 1. Uniform Quantizer

As discussed earlier, a quantizer is called a uniform quantizer if the step size remains constant throughout the input range.

#### Types of Uniform Quantizer

There are two types of uniform quantizers:

(i) Symmetric quantizer of the midtread type

(ii) Symmetric quantizer of the midrise type

• Basically, the quantizer can be of a uniform or non-uniform type. In a uniform quantizer, the representation levels are uniformly spaced; otherwise, the quantizer is non-uniform.

### 2. Non-Uniform Quantizer

• If the quantizer characteristics are non-linear and the steep size is not constant instead if it is variable, dependent o the amplitude of the input signal then the quantization is known as non-uniform quantization.
• In non-uniform quantization, the step size is reduced with the reduction in signal levels. For weak signals, the step size is small, therefore the quantization noise reduces to improve the signal to quantization noise ratio for weak signals.
• The step size is thus varied according to the signal levels to keep the signal-to-noise ratio adequately high. This is non-uniform quantization.
• The non-uniform quantization is practically achieved through a process called companding.

## Quantization Noise | Quantization Error in PCM

Quantization Error (in terms of power) can be given by,

\boxed{Quantization\;Error\;=\frac{{\Delta}^2}{12}}

## Frequently Asked Questions on Quantizer

1. ### What does a quantizer do?

A quantizer auto-corrects the input voltage to the nearest desired target, such as the voltage that corresponds to a semitone or other note in a scale. These are occasionally built into modules like sequencers or oscillators, but quite often they are standalone modules.

2. ### What is a quantizer in communication?

The quantizing of an analog signal is done by discretizing the signal with a number of quantization levels. Quantization is representing the sampled values of the amplitude by a finite set of levels, which means converting a continuous-amplitude sample into a discrete-time signal.

3. ### What is quantization explained?

Quantization is the process of mapping continuous infinite values to a smaller set of discrete finite values. In the context of simulation and embedded computing, it is about approximating real-world values with a digital representation that introduces limits on the precision and range of a value.

4. ### What is quantization in a communication system?

Quantization is the process of mapping continuous amplitude (analog) signals into discrete amplitude (digital) signals. The analog signal is quantized into countable & discrete levels known as quantization levels. Each of these levels represents a fixed input amplitude.

5. ### What is non-uniform quantization?

Uniform Quantization is the type of quantization in which the quantization levels are uniformly spaced is the Uniform Quantization. Nonuniform Quantization is the type of quantization in which the quantization levels are unequal is the Nonuniform

Hello friends, my name is Trupal Bhavsar, I am the Writer and Founder of this blog. I am Electronics Engineer(2014 pass out), Currently working as Junior Telecom Officer(B.S.N.L.) also I do Project Development, PCB designing and Teaching of Electronics Subjects.

This site uses Akismet to reduce spam. Learn how your comment data is processed.