1. Dr. Clincy Professor of CS
Chapter 2 and 3 Handout #2
Dr. Clincy
Professor of CS
Dr. Clincy
Lecture

2. Data Vs Signal
Fully explain the difference between signal and data before getting into the details
(Digital Transmission)
DATA SIGNAL
D D A
(Analog Transmission)
A D
Dr. Clincy
Lecture

3. Data vs Signals
You probably have a good idea about digital and analog signals
What about analog and digital data ??
Analog data examples
Voice
Images
Digital data examples
Text
Digitized voice or images
Dr. Clincy
Lecture

4. Periodic Signal Characteristics
If the signal’s pattern repeats over and over, we called these signals Periodic Signals
Periodic Signals can be either Analog or Digital
Dr. Clincy
Lecture

5. Analog Periodic Signal Case
Amplitude (A): signal value, measured in volts
Frequency (f): repetition rate, cycles per second or Hertz
Period (T): amount of time it takes for one repetition, T=1/f
Phase (f): relative position in time, measured in degrees
General sine wave is written as
S(t) = A sin(2pft + f)
Dr. Clincy
Lecture

6. Varying S(t) = A sin(2pft + f)
Dr. Clincy
Lecture
Note: 45 degrees because p is 180 degrees

7. What is Wavelength ?
The distance an electromagnetic wave can travel in the amount of time it takes to oscillate through a complete cycle
Wavelength (w) = signal velocity x period or propagation speed x period
Recall: period = 1 / frequency
Another perspective of Wavelength: how far did this signal travel AS the signal goes through a FULL cycle ?
Dr. Clincy
Lecture

8. Electromagnetic Signals
Electromagnetic signal can be expressed as a function of time or frequency Function of frequency (more important)
Frequency-Domain Plot – peak amplitudes with respect to frequency
Time-Domain Plot – amplitude changes with respect to time
Different signals
Dr. Clincy
Lecture

9. Electromagnetic Signals - Frequency
Electromagnetic signal can be expressed as a function of time or frequency
Function of frequency (more important)
Spectrum (range of frequencies)
Bandwidth (width of the spectrum)
When we talk about spectrum, we mean
the range of frequencies the
electromagnetic signal takes on
In the example, the signal has a
Frequency range of f to 3f
Therefore, a electromagnetic signal can
be a collection (addition) of periodic analog
Signals (Composite Signal)
Dr. Clincy
Lecture

10. Composite Periodic Signal
According to FOURIER ANALYSIS, a composite signal is a combination of sine waves with different amplitudes, frequencies and phases.
Could converged to a square wave
3rd harmonic
9th harmonic
Dr. Clincy
Lecture

11. Electromagnetic Spectrum for Transmission Media
Tell them how to study this chart
Dr. Clincy
Lecture

12. Digital Signaling represented by square waves or pulses
Refers to transmission of electromagnetic pulses that represents 1’s and 0’s
1 cycle
amplitude (volts)
time
(sec)
frequency (hertz)
= cycles per second
Dr. Clincy
Lecture

13. Digital Signal Rate Each bit’s signal has a certain duration
Example, given a data rate of 50 kbps (or 50,000 bps)
Each would have a 0.02 microseconds duration
Duration (or bit length) = 1/50000 = sec = .02 msec
Dr. Clincy
Lecture

14. Digital Signal # bits per level = log2 of (#oflevels)
Sending 1 bit per level
Sending 2 bits per level
How many levels needed to send 5 bits at a time ????
# bits per level = log2 of (#oflevels)
Dr. Clincy
Lecture

15. Baseband Transmission
In sending the digital signal over channel without changing the digital signal to an analog signal
Use low-pass channel – meaning the bandwidth can be as low as zero
Typical: 2 computers directly connected
In baseband transmission, the required bandwidth is proportional to the bit rate; if we need to send bits faster, we need more bandwidth (the frequency will need to increase)
Dr. Clincy
Lecture

16. Broadband Transmission
Broadband transmission or modulation means changing the digital signal to an analog signal for transmission
Modulation allows us to use a bandpass channel – a channel where the bandwidth doesn’t start at zero
Bandpass channels are more available than low-pass channels
Dr. Clincy
Lecture

17. Channel Capacity
As we know, impairments limits the actual data rate realized
The actual rate realized at which data can be transmitted over a given path, under given conditions is called Channel Capacity
Four concepts
Data rate – the rate, in bps, the data can be communicated
Bandwidth – constrained by the Tx and transport medium – expressed in cycles per second or Hertz
Noise – average level of noise over the communication path
Error rate – the rate in which erroneous bits are received
Dr. Clincy
Lecture

18. Impairments
Dr. Clincy
Lecture

19. Attenuation
Loss of energy – the signal can lose energy as it travels and try to overcome the resistance of the medium
Decibel (dB) is a unit of measure that measures a signal’s lost or gain of strength – can be expressed in power or voltage
dB = 10 log10 [P2/P1] = 20 log10 [V2/V1]
Samples of the power or voltage taken at times 1 and 2.
Dr. Clincy
Lecture

20. Distortion Distortion is when the signal changes its form.
The each signal that makes up a composite signal could have different propagation speeds across the SAME medium – because of this, the different signals could have different delays (arriving at the receiver) – this causes a distortion.
Dr. Clincy
Lecture

21. Noise
Thermal Noise - the uncontrollable or random motion of electrons in the transport medium which creates an extra signal (not sent by the transmitter)
Induced Noise – undesired devices acting as a transmitting antenna and those signals being picked up
Cross Talk Noise – effect of one wire crossing another wire
Impulse Noise – spikes in energy (ie lightning)
Dr. Clincy
Lecture

22. Signal to Noise Ratio SNR = avg-signal-power/avg-noise-power
High SNR – good (less corruption)
Low SNR – bad (more noise than good power)
SNR is described in Decibels (dB)
SNRdB = 10 log10 SNR
Dr. Clincy
Lecture

23. Shannon Equation
Shannon’s equation is used to determine the actual capacity of a channel given noise exist
C = B log2 (1 + SNR)
B = Bandwidth
C= Channel Capacity
SNR = Signal-to-noise ratio
Actual ratio
Dr. Clincy
Lecture

24. Dr. Clincy Professor of CS
Chapter 3 and 4 Handout #3
Dr. Clincy
Professor of CS
Dr. Clincy
Lecture

25. Nyquist Equation Given no noise, determine the maximum bit rate
BitRate = 2 x B x log2 L
B is the bandwidth of the channel
L is the # signal levels used
BitRate unit is bps (bits per second)
Having 2 levels is reliable because a Rx can interpret 2 levels – suppose you had 64 levels – less reliable or more complex to interpret
Dr. Clincy
Lecture

26. Bandwidth Bandwidth is a measure of performance
Bandwidth in hertz – range of frequencies
Bandwidth in bps – bps a channel can handle (D/A case here (ie. Modem))
Dr. Clincy
Lecture

27. Throughput
Throughput is a measure of performance – how fast data can flow through a network
Bandwidth could be what the channel could handle however, Throughput would be the amount that actually flowed through
Bandwidth – potential
Throughput – actual
Dr. Clincy
Lecture

28. Latency
Latency is a performance measure – how long it takes an message to completely arrive to the receiver
Latency consist of
propagation time (time for a bit to travel from Tx to the Rx)
Propagation time = distance/propagation-speed
transmission time (time for a message to be sent)
Transmission time = message-size/bandwidth
queuing time (time each intermediate node holds the message)
processing time (time each node spends processing the message)
Note: if message is small, more bandwidth exists and therefore, the latency is more of propagation time versus transmission time
Dr. Clincy
Lecture

29. The bandwidth-delay product defines the number of bits that can fill the link.
This is important when dealing with “full duplex” and being concerned about sending data to the Rx and receiving acknowledgments back from the Rx at the same time – before sending the next set of data
Dr. Clincy
Lecture

30. Filling the link with bits for case 1
In other words, there can be no more than 5 bits at any time on the link.
Dr. Clincy
Lecture

31. Filling the link with bits in case 2
5 bps
25 bps
In other words, there can be no more than 25 bits at any time on the link.
Dr. Clincy
Lecture

32. Chapter 4: Digital Transmission
Physical Layer Issues
Chapter 4: Digital Transmission
Dr. Clincy
Lecture

33. Data Vs Signal
Fully explain the difference between signal and data before getting into the details
Today’s Lecture (Digital Transmission)
DATA SIGNAL
D D A
Next Lecture (Analog Transmission)
A D
Dr. Clincy
Lecture

34. DIGITAL-TO-DIGITAL CONVERSION
Can represent digital data by using digital signals. The conversion involves three techniques:
line coding – converting bit sequences to signals
block coding – adding redundancy for error detection
scrambling – deals with the long zero-level pulse issue
Line coding is always needed;
Block coding and scrambling may or may not be needed.
Dr. Clincy
Lecture

35. Line coding and decoding
At Tx - Digital data represented as codes is converted to a digital signal via an encoder
At Rx – Digital signal is converted back to digital codes via a decoder
Dr. Clincy
Lecture

36. Signal element versus data element
Data element - smallest entity representing info
Signal element – shortest unit of a digital signal (carriers)
r – is the ratio of # of data elements carried per signal element
Example of adding extra signal elements for synchronization
Example of increasing data rate
Dr. Clincy
Lecture

37. Data Rate Versus Signal Rate
Data rate (or bit rate) - # of data elements (or bits) transmitted in 1 second – bits-per-second is the unit
Signal rate (pulse rate or baud rate) - # of signal elements transmitted in 1 second – baud is the unit
OBJECTIVE ALWAYS: increase data rate while decreasing signal rate – more “bang” for the “buck”
Is it intuitive that if you had a data pattern of all 0s or 1s, it would effect the signal rate ? Therefore to relate data-rate with signal-rate, the pattern matters.
Worst Case Scenario – we need the maximum signaling rate (alternating 1/0s)
Best Case Scenario – we need the minimum signaling rate (all 1/0s)
Focus on average case
S = c x N x 1/r
N – data rate (bps)
c – case factor
S - # of signal elements
r – ratio of data to signal
Dr. Clincy
Lecture

38. Example
A signal is carrying data in which one data element is encoded as one signal element ( r = 1). If the bit rate is 100 kbps, what is the average value of the baud rate if c is between 0 and 1?
Solution
We assume that the average value of c is 1/2 . The baud rate is then
Dr. Clincy
Lecture

39. Bandwidth Now we understand what baud rate is
And we understand what bit rate (or data rate) is
Baud rate - # of carriers on the transport
Data rate - # of passengers (or bits) in the carriers
With this, we clearly see that baud rate effects bandwidth usage
Signaling changes relate to frequency changes – therefore the bandwidth is proportionate with the baud rate:
Bmin = c x N x 1/r or Nmax = 1/c x B x r
minimum bandwidth maximum data rate (given the bandwidth)
N – data rate
C – case factor This formula is consistent with Nyquist formula
r – data to signal ratio
Dr. Clincy
Lecture

40. Example
The maximum data rate of a channel (see Chapter 3) is Nmax = 2 × B × log2 L (defined by the Nyquist formula). Does this agree with the previous formula for Nmax?
Solution
A signal with L levels actually can carry log2L bits per level. If each level corresponds to one signal element and we assume the average case (c = 1/2), then we have
Dr. Clincy
Lecture

41. Decoding Issue 1
Keep in mind the Rx decodes the digital signal – how is it done ?
Rx determines a “moving average” of the signal’s power or voltage levels
This average is called the baseline
Then the Rx compares incoming signal power to this average (or baseline)
If higher than the baseline, could be a 1
If lower than the baseline, could be a 0
In using such a technique, is it intuitive that long runs of 0s or 1s could skew the average (baseline) ?? – this is called baseline wandering (effects Rx’s ability to decode correctly)
Dr. Clincy
Lecture

42. Decoding Issue 2
Effect of lack of synchronization
For the Rx, to correctly read the signal, both the Tx and Rx “bit intervals” must be EXACT
Example of Rx timing off – therefore decoding the wrong data from the signal
To fix this, the Tx could insert timing info into the data that synchs the Rx to the start, middle and end of a pulse – these points could reset an out-of-synch Rx
Dr. Clincy
Lecture

43. Example
In a digital transmission, the receiver clock is 0.1 percent faster than the sender clock. How many extra bits per second does the receiver receive if the data rate is 1 kbps? How many if the data rate is 1 Mbps?
Solution
At 1 kbps, the receiver receives 1001 bps instead of 1000 bps.
At 1 Mbps, the receiver receives 1,001,000 bps instead of 1,000,000 bps.
NOTE: Keep in mind that a FASTER clock means SHORTER intervals
Dr. Clincy
Lecture

44. Line coding scheme categories
Dr. Clincy
Lecture

45. Unipolar NRZ scheme Data Signal Voltages on one side of the axis
Positive voltage signifies 1
Almost zero voltage signifies 0
Power needed to send 1 bit unit of resistance
Dr. Clincy
Lecture

46. Polar NRZ-L and NRZ-I schemes (non-return-to-zero)
change no change
Voltages on both sides of the axis
NRZ-L (level) version – voltage level determines the bit value
NRZ-I (invert) version – voltage change or no-change determines the bit value (no change = 0, change = 1)
Dr. Clincy
Lecture

47. Polar RZ scheme Uses 3 values: positive, negative and zero
Signal changes Not between bits BUT during the bit
H-to-L in middle for 1
L-to-H in middle for 0
Positioning occurs at the beginning of the period
Dr. Clincy
Lecture

48. Polar biphase: Manchester and Differential Manchester Schemes
Manchester: H-to-L=0, L-to-H=1
Differential Manchester: H-to-L or L-to-H at begin=0, No change at begin=1
Dr. Clincy
Lecture

49. Bipolar schemes: AMI and pseudoternary
Bipolar encoding uses 3 voltage levels: positive, negative and zero.
One data element is at ZERO, while the others alternates between negative and positive
Alternate Mark Inversion (AMI) scheme – neutral zero voltage is 0 and alternating positive and negative voltage represents 1
Pseudoternary scheme – vice versa from the AMI scheme
Dr. Clincy
Lecture

50. Multilevel Schemes
These schemes attempt to increase the number of bits per baud
Given m data elements, could produce 2m data patterns
Given L levels, could produce Ln combinations of signal patterns (where n is the length of the signal patterns)
If 2m = Ln, each data pattern is encoded into one signal pattern (1-to-1)
If 2m < Ln, data patterns use a subset of signal patterns – could use the extra signal patterns for fixing baseline wandering and error detection
Classify these codes as mBnL where:
m – length of the binary pattern
B – means Binary data
n – length of the signal pattern
L - # signaling levels (letters in place of L: B=2, T=3 and Q=4)
Dr. Clincy
Lecture

51. Multilevel: 2B1Q scheme 2B1Q Data patterns of size 2 bits
Encodes 2-bit patterns in one signal element
4 levels of signals
If previous level was positive and the next level becomes +3, represents 01
If previous level was positive and the next level becomes -3, represents 11
Dr. Clincy
Lecture

52. Multilevel: 8B6T scheme Data patterns of size 8 bits
Encodes 8-bit patterns in six signal elements
Using 3 levels of signal
Dr. Clincy
Lecture

53. Multilevel: 4D-PAM5 scheme
4-dimensional five-level pulse amplitude modulation scheme
Instead of transmitting in serial form – parts of the code are in sent in parallel over 4 wires (versus 1 wire)
In this particular case, it would take ¼ less time to transmit
Dr. Clincy
Lecture

54. Multitransition: MLT-3 scheme
Multi-line transmission, three-level scheme
Uses three levels and three transition rules to jump between levels:
- if the next bit is 0, there is no transition
- if the next bit is 1 and the current level is not 0, the next level is 0
- if the next bit is 1 and the current level is 0, the next level is the opposite of the last nonzero level
Dr. Clincy
Lecture