Digital Communications Prof. Sandeep J. Rajput Assistant Professor E & C Engg. Dept. HCET,Sidhpur.
-
Upload
nathan-hopkins -
Category
Documents
-
view
214 -
download
1
Transcript of Digital Communications Prof. Sandeep J. Rajput Assistant Professor E & C Engg. Dept. HCET,Sidhpur.
Digital Communications
Prof. Sandeep J. RajputAssistant ProfessorE & C Engg. Dept.HCET,Sidhpur
Overview
• Introduction– Communication systems– Digital communication system– Importance of Digital transmission
• Basic Concepts in Signals– Sampling– Quantization– Coding
2Digital 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
3Digital Communication
Communication Systems
Communication System
TransmitterSource“Sending Point”
ReceiverSink“Receiving Point”
4Digital Communication
Information Source
Transmitter Channel Receiver Information Sink
Block Diagram of a typical communication system
Communication Systems
5Digital Communication
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
6Digital Communication
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
7Digital Communication
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 8Digital Communication
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
9Digital Communication
Effect of noise on transmitted signal
10Digital Communication
Digital Communication System
Information Source
A / D Converter
Source Encoder
ChannelEncoder
Modulator
Information Sink
D / AConverter
SourceDecoder
ChannelDecoder Demodulator
Channel
11Digital Communication
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 signal12Digital Communication
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
13Digital Communication
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
Modulator14Digital Communication
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
15Digital Communication
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 16Digital Communication
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
17Digital 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.
18Digital Communication
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.
)4510002sin(2)( ttv
19Digital Communication
Time domain Vs. Frequency domain
Time Domain F
ourier/Laplace Transform
Frequency Domain
Fourier/Laplace Transform
20Digital Communication
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…
21Digital Communication
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.
22Digital Communication
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
dtetxfX ftj 2)()(
dfefXtx ftj 2)()(
Fourier TransformTime domain Frequency Domain
Inverse Fourier TransformFrequency domain Time Domain
23Digital 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.
f
fee
fjdtedtetxfX ftjftjftjftj
)sin(
2
1)()(
5.0
5.0
5.05.022
Time Domain Frequency Domain
Amp. Amp.
Time(s)
Frequency (Hz)
24Digital 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 SignalPositive = Negative 25Digital Communication
Converting an Analog Signal to a Discrete Signal (A/D)
• Can be done through three basic steps:
1- Sampling
2- Quantization
3- Coding26Digital 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
27Digital Communication
Sampling
Original Analog Signal“Before Sampling”
Sampled Analog Signal“After Sampling”
28Digital 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?
29Digital 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
Ts 1
2 fmax
30Digital 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
31Digital Communication
Quantization
• Dynamic range of a signal– The difference between the highest to lowest value
the signal can takes.
32Digital 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.
33Digital 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]
34Digital Communication
Quantization
• For every level, we assign a value for the signal if it falls within the same level.
M1 = 1.25 if the signal in m1
M2 = 3.75 if the signal in m2Q [ v(t) ] =
M3 = 6.25 if the signal in m3
M4 = 8.75 if the signal in m4
35Digital Communication
Quantization
Original Analog Signal“Before Quantization”
Quantized Analog Signal“After Quantization” 36Digital Communication
Quantization
Original Discrete Signal“Before Quantization”
Quantized Discrete Signal“After Quantization” 37Digital 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.
Dynamic Range
No. of Quantization levels
Smax Smin
L
38Digital 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 Step Code Step Code Step Code
0 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
39Digital 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.
40Digital Communication
THANKS…..
Digital Communication 41