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SIGNAL PROPAGATION
Lecture 2
Dr. Razi Iqbal
[email protected]
Signal Transmission
• A signal can be anything
• A hand motion
• A Text
• Audible
• The data in a network is transferred using electrical signals.
• The information flows within a medium through an electric current.
• The information sent by the user is converted into electrical signals
by a means called Encoding or Modulation
• There are two types of signals in a network
• Digital Signals
• Analog Signals
Digital Signals
• Digital signals are discrete and consist of On / Off or 1 / 0
• The data is encoded using different techniques
• Current state encoding
• State-transition encoding
• Current State Encoding
• Data is encoded by presence or absence of a signal state
• Signal state can be 0 or 1
• Signal is monitored by network devices to determine the
current state of the signal.
Digital Signals
Current State Encoding
• Unipolar
• One polarity is used
• Level 0 is 1 and one of the polarities is 0
• It is the simplest kind of encoding
• Very inexpensive
0
+5V
0
0
0
0
0
1
1
1
1
1
1
1
1
-5V
0
0
0
0
Unipolar
Draw with positive polarity
1
0
1
0
0
1
1
0
Unipolar
Draw with positive polarity
1
0
1
0
0
0
0
1
0
0
+5V
0
1
1
1
1
1
0
Digital Signals
Current State Encoding
• Polar
• Both polarities are used (-ve and +ve)
• Positive is 1 and Negative is 0 or Negative is 1 and Positive is 0.
Polar
• 1 is positive
• 0 is negative
1
0
1
0
0
1
1
0
Polar
• 1 is positive
• 0 is negative
1
0
+5V
1
1
0
0
1
1
1
1
0
-5V
0
0
0
0
1
0
Digital Signals
Current State Encoding
• Return to Zero
• After transmission of each bit, voltage returns to zero
• At middle 0, the condition is a rest condition
• +ve voltage can be 1 and –ve can be zero
+5V
-5V
Return to Zero
• 1 is positive
• 0 is negative
1
0
1
0
0
1
1
0
Return to Zero
• 1 is positive
• 0 is negative
1
0
+5V
1
1
0
0
1
1
1
1
1
0
-5V
0
0
0
0
0
Digital Signals
• State-Transition Encoding
• Transition in signal is used to represent data.
• High to low transition can be 1
• Low to High transition can be 0
• Examples are
• Non-Return-To-Zero
• Manchester
• Differential Manchester
Digital Signals
State Transition Encoding
• Manchester
• Low to high mid-bit transition is 0
• High to low mid-bit transition is 1
Manchester
• Low to high is 0
• High to low is 1
1
0
1
0
0
1
1
0
Manchester
• Low to high is 0
• High to low is 1
1
0
1
0
0
1
1
0
Digital Signals
State Transition Encoding
• Differential Manchester
• If transition in a mid-bit is done at the start of a bit interval, its 0 , else 1
• Since it’s a bi-phase, so transition is must.
Differential Manchester
• If transition occurs, its 0
• If transition does not occur, its 1
1
0
1
0
0
1
1
0
Differential Manchester
• If transition occurs, its 0
• It transition does not occur, its 1
1
0
1
0
0
1
1
0
Analog Signals
• Analog signals consist of electromagnetic waves
• This wave is constantly changing
• It changes from high to low or low to high
• It looks like a sine wave
Frequency
Amplitude
Analog Signals
Amplitude
• Amplitude is the strength of the signal
• Amplitude is the height of the wave
• It is represented as
• Volts in electrical Potential
• Amps for electric current
• Watts for electric power
Different Amplitudes
Analog Signals
Frequency
• Amount of time a wave takes to complete one cycle
• If a signal takes 1 sec to go from high to low and then back
to high, the frequency is 1
• It is measured in Hz or cycle per second.
Analog Signal Modulation
• Carriers send signal continuously in a stream then how data
is transferred?
• Data is transferred using
• Amplitude
• Frequency
Three Degrees of Freedom
• Phase
• If amplitude is High bit is 1 and if low bit is 0
• If frequency is High bit is 1 and if low bit is 0
• This detection of high and low is done by network devices.
Analog Signal Modulation
Amplitude Modulation
• Height of wave sends the information.
• ASCII ‘A’ (65) in binary ‘01000001’
• Below is representation of A in binary as AM
Amplitude Modulation
1
0
1
0
0
1
1
0
Amplitude Modulation
1
0
1
0
0
1
1
0
Analog Signal Modulation
Frequency Modulation
• No. of waves per cycle to send information.
• ASCII ‘A’ (65) in binary ‘01000001’
• Below is representation of A in binary as FM
Frequency Modulation
1
0
1
0
0
1
1
0
Frequency Modulation
1
0
1
0
0
1
1
0
Strategies for Encoding
Amplitude Shift Keying (ASK)
• Higher waves are 1 and lower are 0
• Sometimes 0 voltage or no voltage is 0 and some
voltage is 1.
• ASCII ‘A’ (65) in binary ‘01000001’
• Below is representation of A in binary as ASK
Strategies for Encoding
Frequency Shift Keying (FSK)
• More waves are 1 and less are 0
• ASCII ‘A’ (65) in binary ‘01000001’
• Below is representation of A in binary as FSK
Strategies for Encoding
Phase Shift Keying (FSK)
• Phases of waves relative to other are used in this case
• ASCII ‘A’ (65) is binary ‘01000001’
• Below is representation of A in binary as PSK
Channel Capacity
• The maximum rate at which data can pass a specific
communication medium under given circumstances is
called Channel Capacity.
• Below are four important concepts: • Data Rate
• Bandwidth
• Noise
• Error Rate
Channel Noise
• A noise is a phenomenon that occurs in wireless
channel due to hindrance or disturbance.
• This disturbance or hindrance is due to many internal or
external factors.
• Noise can occur because of
• Physical properties of the communication medium
• Power limitation of sender or receiver
• Hindrance due to physical objects.
Nyquist Bandwidth
• In an ideal world where there is no noise bandwidth and
signal rate have ideal relationship.
• According to Nyquist, if Bandwidth is B, the maximum signal
rate that can be carried is 2B.
• It means in ideal scenario a Bandwidth is a full Sine wave.
• Bandwidth will hence contain 2 bits, one high and one low.
• Hence a channel capacity will be
C = 2B
Shannon Capacity Formula
• The environment is not always ideal.
• Noise is always there which affects the wireless
communication.
• Presence of noise can corrupt the bits.
• If data rate is high, bits are higher and hence chances
of data corruption is high.
Shannon Capacity Formula
• According to Claude Shannon, greater signal strength
can improve the receiving of data at client.
• The most important factor is Signal-to-Noise Ration
(SNR).
• Ratio of power in the signal and the power contained in the
noise.
• Normally this power is measured at the receiver.
• For a good connection, SNR must be higher.
Signal to Noise Ratio (SNR)
• For a good wireless communication, signal power should be
greater than noise power.
• For voice communication, the value of SNR must be around 20db.
• SNR > 40 is expected to be an excellent connection.
• A –ve value means no communication.
Finding SNR from SNRdB
Shannon Capacity Formula
• Shannon’s formula provides a mechanism of getting
maximum channel capacity in bits per second, given
bandwidth and SNR.
• Below is the Shannon Formula: -
Shannon Capacity Formula
• Provided the SNRdb = 24dB and bandwidth of 1Mhz,
calculate the maximum channel capacity using
Shannon’s formula.