1. Digital Communications
Prof. Sandeep J. Rajput
Assistant Professor
E & C Engg. Dept.
HCET,Sidhpur

2. Digital Communication
Overview
Introduction
Communication systems
Digital communication system
Importance of Digital transmission
Basic Concepts in Signals
Sampling
Quantization
Coding
Digital Communication

3. Digital Communication
What is Communication?
Communication is transferring data reliably from one point to another
Data could be: voice, video, codes etc…
It is important to receive the same information that was sent from the transmitter.
Communication system
A system that allows transfer of information reliably
Digital Communication

4. Communication Systems
Transmitter
Source
“Sending Point”
Receiver
Sink
“Receiving Point”
Communication
System
Digital Communication

5. Communication Systems
Information Source
Transmitter
Channel
Receiver
Information Sink
Block Diagram of a typical communication system
Digital Communication

6. Communication Systems
Information Source
The source of data
Data could be: human voice, data storage device CD, video etc..
Data types:
Discrete: Finite set of outcomes “Digital”
Continuous : Infinite set of outcomes “Analog”
Transmitter
Converts the source data into a suitable form for transmission through signal processing
Data form depends on the channel
Digital Communication

7. Communication Systems
Channel:
The physical medium used to send the signal
The medium where the signal propagates till arriving to the receiver
Physical Mediums (Channels):
Wired : twisted pairs, coaxial cable, fiber optics
Wireless: Air, vacuum and water
Each physical channel has a certain limited range of frequencies ,( fmin  fmax ), that is called the channel bandwidth
Physical channels have another important limitation which is the NOISE
Digital Communication

8. Communication Systems
Noise is undesired random signal that corrupts the original signal and degrades it
Noise sources:
Electronic equipments in the communication system
Thermal noise
Atmospheric electromagnetic noise (Interference with another signals that are being transmitted at the same channel)
Another Limitation of noise is the attenuation
Weakens the signal strength as it travels over the transmission medium
Attenuation increases as frequency increases
One Last important limitation is the delay distortion
Mainly in the wired transmission
Delays the transmitted signals  Violates the reliability of the communication system
Digital Communication

9. Communication Systems
Receiver
Extracting the message/code in the received signal
Example :
Speech signal at transmitter is converted into electromagnetic waves to travel over the channel
Once the electromagnetic waves are received properly, the receiver converts it back to a speech form
Information Sink
The final stage
The user
Digital Communication

10. Effect of noise on transmitted signal
Digital Communication

11. Digital Communication System
Information Source
A / D
Converter
Source
Encoder
Channel
Encoder
Modulator
Channel
Source
Decoder
Channel
Decoder
Information Sink
D / A
Converter
Demodulator
Digital Communication

12. Digital Communication System
Information source
Analog Data: Microphone, speech signal, image, video etc…
Discrete (Digital) Data: keyboard, binary numbers, hex numbers, etc…
Analog to Digital Converter (A/D)
Sampling:
Converting continuous time signal to a digital signal
Quantization:
Converting the amplitude of the analog signal to a digital value
Coding:
Assigning a binary code to each finite amplitude in the analog signal
Digital Communication

13. Digital Communication System
Source encoder
Represent the transmitted data more efficiently and remove redundant information
How? “write Vs. rite”
Speech signals frequency and human ear “20 kHz”
Two types of encoding:
Lossless data compression (encoding)
Data can be recovered without any missing information
Lossy data compression (encoding)
Smaller size of data
Data removed in encoding can not be recovered again
Digital Communication

14. Digital Communication System
Channel encoder:
To control the noise and to detect and correct the errors that can occur in the transmitted data due to the noise.
Modulator:
Represent the data in a form to make it compatible with the channel
Carrier signal “high frequency signal”
Demodulator:
Removes the carrier signal and reverse the process of the Modulator
Digital Communication

15. Digital Communication System
Channel decoder:
Detects and corrects the errors in the signal gained from the channel
Source decoder:
Decompresses the data into it’s original format.
Digital to Analog Converter:
Reverses the operation of the A/D
Needs techniques and knowledge about sampling, quantization, and coding methods.
Information Sink
The User
Digital Communication

16. Why should we use digital communication?
Ease of regeneration
Pulses “ 0 , 1”
Easy to use repeaters
Noise immunity
Better noise handling when using repeaters that repeats the original signal
Easy to differentiate between the values “either 0 or 1”
Ease of Transmission
Less errors
Faster !
Better productivity
Digital Communication

17. Why should we use digital communication?
Ease of multiplexing
Transmitting several signals simultaneously
Use of modern technology
Less cost !
Ease of encryption
Security and privacy guarantee
Handles most of the encryption techniques
Digital Communication

18. Digital Communication
Disadvantage !
The major disadvantage of digital transmission is that it requires a greater transmission bandwidth or channel bandwidth to communicate the same information in digital format as compared to analog format.
Another disadvantage of digital transmission is that digital detection requires system synchronization, whereas analog signals generally have no such requirement.
Digital Communication

19. Basic Concepts in Signals
A/D is the process of converting an analog signal to digital signal, in order to transmit it through a digital communication system.
Electric Signals can be represented either in Time domain or frequency domain.
Time domain i.e
We can get the value of that signal at any time (t) by substituting in the v(t) equation.
Digital Communication

20. Time domain Vs. Frequency domain
Digital Communication

21. Time domain Vs. Frequency domain
Consider taking two types of images of a person:
Passport image
X-Ray image
Two different domains, spatial domain “passport image” and “X-Ray domain”.
Doctors are taking the image in the X-Ray domain to extract more information about the patient.
Different domains helps fetching and gaining knowledge about an object.
An Object : Electric signal, human body, etc…
Digital Communication

22. Time domain Vs Frequency domain
We deal with communication system in the time domain.
Lack of information about the signal
Complex analysis
Frequency domain gives us the ability to extract more information about the signal while simplifying the mathematical analysis.
Digital Communication

23. Frequency Domain
To study the signal in the frequency domain, we need to transfer the original signal from the time domain into the frequency domain.
Using Fourier Transform
Fourier Transform
Time domain  Frequency Domain
Inverse Fourier Transform
Frequency domain  Time Domain
Digital Communication

24. Digital Communication
Spectrum
The spectrum of a signal is a plot which shows how the signal amplitude or power is distributed as a function of frequency.
Amp.
Amp.
Time(s)
Frequency (Hz)
Digital Communication
Time Domain
Frequency Domain

25. Digital Communication
Band limited signals
A band limited signal is a signal who has a finite spectrum.
Most of signal energy in the spectrum is contained in a finite range of frequencies.
After that range, the signal power is almost zero or negligible value.
X(f)
+ fH
- fH
Freq.
Symmetrical Signal
Positive = Negative
Digital Communication

26. Converting an Analog Signal to a Discrete Signal (A/D)
Can be done through three basic steps:
1- Sampling
2- Quantization
3- Coding
Digital Communication

27. Digital Communication
Sampling
Process of converting the continuous time signal to a discrete time signal.
Sampling is done by taking “Samples” at specific times spaced regularly.
V(t) is an analog signal
V(nTs) is the sampled signal
Ts = positive real number that represent the spacing of the sampling time
n = sample number integer
Digital Communication

28. Sampling Original Analog Signal “Before Sampling”
Sampled Analog Signal
“After Sampling”
Digital Communication

29. Digital Communication
Sampling
The closer the Ts value, the closer the sampled signal resemble the original signal.
Note that we have lost some values of the original signal, the parts between each successive samples.
Can we recover these values? And How?
Can we go back from the discrete signal to the original continuous signal?
Digital Communication

30. Digital Communication
Sampling Theorem
A band limited signal having no spectral components above fmax (Hz), can be determined uniquely by values sampled at uniform intervals of Ts seconds, where
An analog signal can be reconstructed from a sampled signal without any loss of information if and only if it is:
Band limited signal
The sampling frequency is at least twice the signal bandwidth
Digital Communication

31. Digital Communication
Quantization
Quantization is a process of approximating a continuous range of values, very large set of possible discrete values, by a relatively small range of values, small set of discrete values.
Continuous range  infinite set of values
Discrete range  finite set of values
Digital Communication

32. Digital Communication
Quantization
Dynamic range of a signal
The difference between the highest to lowest value the signal can takes.
Digital Communication

33. Digital Communication
Quantization
In the Quantization process, the dynamic range of a signal is divided into L amplitude levels denoted by mk, where k = 1, 2, 3, .. L
L is an integer power of 2
L = 2k
K is the number of bits needed to represent the amplitude level.
For example:
If we divide the dynamic range into 8 levels,
L = 8 = 23
We need 3 bits to represent each level.
Digital Communication

34. Digital Communication
Quantization
Example:
Suppose we have an analog signal with the values between [0, 10]. If we divide the signal into four levels. We have
m1  [ 0, 2.5 ]
m2  [ 2.5, 5 ]
m3  [ 5 , 7.5]
m4  [ 7.5, 10]
Digital Communication

35. Digital Communication
Quantization
For every level, we assign a value for the signal if it falls within the same level.
M1 = if the signal in m1
M2 = if the signal in m2
Q [ v(t) ] =
M3 = if the signal in m3
M4 = if the signal in m4
Digital Communication

36. Quantization Original Analog Signal “Before Quantization”
Quantized Analog Signal
“After Quantization”
Digital Communication

37. Quantization Original Discrete Signal “Before Quantization”
Quantized Discrete Signal
“After Quantization”
Digital Communication

38. Digital Communication
Quantization
The more quantization levels we take the smaller the error between the original and quantized signal.
Quantization step
The smaller the Δ the smaller the error.
Digital Communication

39. Digital Communication
Coding
Assigning a binary code to each quantization level.
For example, if we have quantized a signal into 16 levels, the coding process is done as the following:
Step
Code
0000 4
0100 8
1000 12
1100 1
0001 5
0101 9
1001 13
1101 2
0010 6
0110 10
1010 14
1110 3
0011 7
0111 11
1011 15
1111
Digital Communication

40. Digital Communication
Coding
The binary codes are represented as pulses
Pulse means 1
No pulse means 0
After coding process, the signal is ready to be transmitted through the channel. And Therefore, completing the A/D conversion of an analog signal.
Digital Communication

41. Digital Communication
THANKS…..
Digital Communication