Digital Communication - Line Codes

A line code is the code used for data transmission of a digital signal over a transmission line. This process of coding is chosen so as to avoid overlap and distortion of signal such as inter-symbol interference.

Properties of Line Coding

Following are the properties of line coding −

Types of Line Coding

There are 3 types of Line Coding

Unipolar Signaling

Unipolar signaling is also called as On-Off Keying or simply OOK.

The presence of pulse represents a 1 and the absence of pulse represents a 0.

There are two variations in Unipolar signaling −

Unipolar Non-Return to Zero (NRZ)

In this type of unipolar signaling, a High in data is represented by a positive pulse called as Mark, which has a duration T0 equal to the symbol bit duration. A Low in data input has no pulse.

The following figure clearly depicts this.

NRZ

The advantages of Unipolar NRZ are −

Disadvantages

The disadvantages of Unipolar NRZ are −

Unipolar Return to Zero (RZ)

In this type of unipolar signaling, a High in data, though represented by a Mark pulse, its duration T0 is less than the symbol bit duration. Half of the bit duration remains high but it immediately returns to zero and shows the absence of pulse during the remaining half of the bit duration.

It is clearly understood with the help of the following figure.

Unipolar Return to Zero

The advantages of Unipolar RZ are −

Disadvantages

The disadvantages of Unipolar RZ are −

Polar Signaling

There are two methods of Polar Signaling. They are −

Polar NRZ

In this type of Polar signaling, a High in data is represented by a positive pulse, while a Low in data is represented by a negative pulse. The following figure depicts this well.

Polar NRZ

The advantages of Polar NRZ are −

Disadvantages

The disadvantages of Polar NRZ are −

Polar RZ

In this type of Polar signaling, a High in data, though represented by a Mark pulse, its duration T0 is less than the symbol bit duration. Half of the bit duration remains high but it immediately returns to zero and shows the absence of pulse during the remaining half of the bit duration.

However, for a Low input, a negative pulse represents the data, and the zero level remains same for the other half of the bit duration. The following figure depicts this clearly.

Polar RZ

The advantages of Polar RZ are −

Disadvantages

The disadvantages of Polar RZ are −

Bipolar Signaling

This is an encoding technique which has three voltage levels namely +, - and 0. Such a signal is called as duo-binary signal.

An example of this type is Alternate Mark Inversion (AMI). For a 1, the voltage level gets a transition from + to – or from – to +, having alternate 1s to be of equal polarity. A 0 will have a zero voltage level.

Even in this method, we have two types.

From the models so far discussed, we have learnt the difference between NRZ and RZ. It just goes in the same way here too. The following figure clearly depicts this.

Bipolar Signaling

The above figure has both the Bipolar NRZ and RZ waveforms. The pulse duration and symbol bit duration are equal in NRZ type, while the pulse duration is half of the symbol bit duration in RZ type.

Advantages

Following are the advantages −

Disadvantages

Following are the disadvantages −

Power Spectral Density

The function which describes how the power of a signal got distributed at various frequencies, in the frequency domain is called as Power Spectral Density (PSD).

PSD is the Fourier Transform of Auto-Correlation (Similarity between observations). It is in the form of a rectangular pulse.

Power Spectral Density

PSD Derivation

According to the Einstein-Wiener-Khintchine theorem, if the auto correlation function or power spectral density of a random process is known, the other can be found exactly.

Hence, to derive the power spectral density, we shall use the time auto-correlation $(R_x(\tau))$ of a power signal $x(t)$ as shown below.

Since $x(t)$ consists of impulses, $R_x(\tau)$ can be written as

$R_x(\tau) = \frac\displaystyle\sum\limits_^\infty R_n\delta(\tau - nT)$

Getting to know that $R_n = R_$ for real signals, we have

$S_x(w) = \frac(R_0 + 2\displaystyle\sum\limits_^\infty R_n \cos nwT)$

Since the pulse filter has the spectrum of $(w) \leftrightarrow f(t)$, we have

$s_y(w) = \mid F(w) \mid^2S_x(w)$

$= \frac<\mid F(w) \mid^2>(R_0 + 2\displaystyle\sum\limits_^\infty R_n \cos nwT)$

Hence, we get the equation for Power Spectral Density. Using this, we can find the PSD of various line codes.