Line Coding And Types
LINE CODE :
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
- As the coding is done to make more bits transmit on a single signal, the bandwidth used is much reduced.
- For a given bandwidth, the power is efficiently used.
- The probability of error is much reduced.
- Error detection is done and the bipolar too has a correction capability.
- Power density is much favorable.
- The timing content is adequate.
- Long strings of 1s and 0s is avoided to maintain transparency.
Types of Line Coding
- Unipolar
- Polar
- Bi-polar
- Unipolar Signaling
The presence of pulse represents a 1 and the absence of pulse represents a 0.
There are two variations in Unipolar signaling −
- Non Return to Zero
- Return to Zero
Unipolar Non-Return to Zero
- It is simple.
- A lesser bandwidth is required.
- No error correction done.
- Presence of low frequency components may cause the signal droop.
- No clock is present.
- Loss of synchronization is likely to occur (especially for long strings of 1s and 0s).
Unipolar Return to Zero
- It is simple.
- The spectral line present at the symbol rate can be used as a clock.
The disadvantages of Unipolar RZ are −
- No error correction.
- Occupies twice the bandwidth as unipolar NRZ.
- The signal droop is caused at the places where signal is non-zero at 0 Hz.
Polar Signaling
There are two methods of Polar Signaling. They are −
- Polar NRZ
- Polar RZ
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.
Advantages
The advantages of Polar NRZ are −
- It is simple.
- No low-frequency components are present.
Disadvantages
The disadvantages of Polar NRZ are −
No error correction.
No clock is present.
The signal droop is caused at the places where the signal is non-zero at 0 Hz.
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.
Advantages
The advantages of Polar RZ are −
- It is simple.
- No low-frequency components are present.
Disadvantages
The disadvantages of Polar RZ are −
No error correction.
No clock is present.
Occupies twice the bandwidth of Polar NRZ.
The signal droop is caused at places where the signal is non-zero at 0 Hz.
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 . 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.
- Bipolar NRZ
- Bipolar RZ
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.
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 −
It is simple.
No low-frequency components are present.
Occupies low bandwidth than unipolar and polar NRZ schemes.
This technique is suitable for transmission over AC coupled lines, as signal drooping doesn’t occur here.
A single error detection capability is present in this.
Disadvantages
Following are the disadvantages −
- No clock is present.
- Long strings of data causes loss of synchronization.
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 of a power signal as shown below.
Since consists of impulses, can be written as
Where
Getting to know that for real signals, we have
Since the pulse filter has the spectrum of , we have
Hence, we get the equation for Power Spectral Density. Using this, we can find the PSD of various line codes.
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