Module 3

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Module 3

• Data Communication Part I

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• Textbook sections
• LG 3.1 Digital Representation of Information
• LG3.2 Why Digital communication?
• LG 3.3 Characterization of Communication Channels
• LG 3.4 Fundamental Limits in Digital Transmission
• LG 3.5 Line Coding
• LG 3.6 Modems and Digital Modulation
• Topics
• Data and Signals
• Data
• Signals
• Line Coding
• Modems
• Baseband and Broadband
• Synchronous and Asynchronous Communication
• Advantages of Digital Communication
• Fundamental Limits in Digital Transmission
• Nyquist Rate
• Shannons channel coding theorem

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1. Data and Signals

• Data Entities that convey meaning
• Analog data are functions of time and occupy a
  limited frequency spectrum
• Digital data
• Examples pressure, temperature
• Signals Electric or electromagnetic encoding of
  data
• Analog signal time-varying electromagnetic
  signal occupying a limited frequency spectrum
• Digital signal Using a different voltage level
  for each of the two binary digits.
• Representation
• Frequency domain representations of data and
  signals
• Time domain representations of data and signals

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1. Data and Signals

• Representations

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Time domain and frequency domain representations
of signals
Time domain
Frequency domain
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1. Data and Signals

• Line Coding
• The method used for converting a binary
  information sequence into a digital signal in a
  digital communications system
• Mapping from data bits to voltage pulses
• Types of digital-to-digital encoding
• Unipolar The voltage pulses all have the same
  algebraic sign, that is, all positive or
  negative. Only one level of value.
• Polar signaling One logic state is represented
  by a positive voltage level, and the other by a
  negative voltage level. Two levels (positive and
  negative) of amplitude.
• Nonreturn to zero (NRZ) The voltage level is
  constant during a bit interval. There is no
  transition. (no return to a zero voltage level)
• Differential encoding The signal is decoded by
  comparing the polarity of adjacent voltage pulses
  rather than the absolute values of a voltage
  pulse.
• Biphase At least one transition exists per bit
  interval.
• Bipolar Three levels of amplitude (positive,
  zero, and negative)

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Types of digital-to-digital encoding
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(No Transcript)
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1. Data and Signals

• Applications of Line Coding
• NRZ encoding RS232 based protocols
• Manchester encoding Ethernet networks
• Differential Manchester encoding token-ring
  networks
• NRZ-Inverted encoding Fiber Distributed Data
  Interface (FDDI)

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1. Data and Signals

• Line Coding Format

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LG Figure 3.25 Line coding methods
0
1
0
1
1
1
0
0
1
Unipolar NRZ
Polar NRZ
NRZ-Inverted (Differential Encoding)
Bipolar Encoding
Manchester Encoding
Differential Manchester Encoding
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1. Data and Signals

• Line coding considerations
• Synchronization (more detail next page)
• A signal change for each bit can assure
  synchronization. The receiver can use these
  changes to build up, update, and synchronize its
  clock.
• Bandwidth
• Signal changes needed to encode one bit.
• Direct Current (DC) component (less important)
• Related to using transformers
• Problem associated with NRZ coding

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1. Data and Signals

• FDDI 4B/5B
• Address the inefficiency of the Manchester
  encoding without suffering from the problem of
  having extended durations of high or low signals.
• The idea of 4B/5B is to insert extra bits into
  the bit stream so as to break up long sequences
  of 0s or 1s. Specially, every 4 bits of actual
  data are encoded in a 5 bit code that is then
  transmitted to the receiver hence the name
  4B/5B.
• The 5 bits are selected in such a way that each
  symbol has no more than one leading 0 and no more
  than two trailing 0s. Thus when sent
  back-to-back, no pair of 5 bit codes results in
  more than three consecutive 0s being transmitted.
• The resulting 5 bit codes are then transmitted
  using the NRZI encoding, which explains why the
  code is only concerned about consecutive 0s -
  NRZI already solves the problem of consecutive
  1s.
• The 4B/5B results in 80 efficiency.

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1. Data and Signals
4-bit Data Symbol -gt 5-bit Code Bits -gt encoding
each code bit using NRZ-I
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1. Data and Signals

• Synchronization Consideration
• Problem of unvarying signal
• When a signal is unvarying, the receiver cannot
  determine the beginning and ending of each bit.
• Take unipolar coding for example. A long
  uninterrupted series of 1s or 0s can cause
  synchronization problem.
• Problem of Using Timers
• Whenever there is no signal change to indicate
  the start of the next bit in a sequence, the
  receiver has to rely on a timer. Given an
  expected bit rate of 1000 bps, if the receiver
  detects a positive voltage lasting 0.005 seconds,
  it reads one 1 per 0.001 seconds, or five 1s.
  However, five 1s can be stretched to 0.006
  second, causing an extra 1 bits to be read by the
  receiver. That one extra bit in the data stream
  causes everything after it to be decoded
  erroneously.
• Problem of Having a Separate Clock Line
• A solution developed to control the
  synchronization of unipolar transmission is to
  use a separate, parallel line that carries a
  clock pulse and allows the receiving device to
  resynchronize its timer to that of the signals.
  But doubling the number of lines used for
  transmission increase the cost.

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1. Data and Signals

• Modem
• A communications device that enables a computer
  to transmit information over a standard telephone
  line. Because a computer is digital, it works
  with discrete electrical signals representing
  binary 1 and binary 0. A telephone is analog and
  carries a signal that can have any of a large
  number of variations. Modems are needed to
  convert digital signals to analog, and vice
  versa. When transmitting, modems
  impose(modulate) a computers digital signals on
  a continuous carries frequency on the telephone.
  When receiving, modems sift out (demodulate) the
  information from the carries and transfer it in
  digital form to the computer.
• Basic function of the modulation is to produce a
  signal that contains the information sequence and
  that occupies frequencies in the range passed by
  the channel.

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LG Figure 3.28 Amplitude, frequency, and phase
modulation techniques
Information
1
(a)
Amplitude Shift Keying
t
-1
1
Frequency Shift Keying
(b)
t
-1
1
Phase Shift Keying
(c)
t
-1
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LG Figure 3.29 Modulating a signal
(a) Information
A
(b) Baseband Signal Xi(t)
t
2T
6T
T
4T
5T
3T
0
-A
t
2A
(d) 2Yi(t) cos(2?fct)
t
-2A
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LG Figure 3.30 Modulator and demodulator
(a) Modulate cos(2?fct) by multiplying it by Ak
for (k-1)T lt t ltkT
x
Ak
Yi(t) Ak cos(2?fct)
cos(2?fct)
(b) Demodulate (recover) Ak by multiplying by
2cos(2?fct) and lowpass filtering
Lowpass Filter with cutoff W Hz
x
Yi(t) Akcos(2?fct)
Xi(t)
2cos(2?fct)
2Ak cos2(2?fct) Ak 1 cos(2??fct)
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1. Data and Signals

• Baseband Technology
• A network technology that uses a small part of
  the electromagnetic spectrum and sends one signal
  at a time over the underlying medium.
• Uses digital signaling. Digital signals are
  inserted on the line as voltage pulses.
• The entire frequency spectrum of the medium is
  used to form the signal hence frequency-division
  multiplexing (FDM) cannot be used
• Transmission is bidirectional. That is, a signal
  inserted at any point on the medium propagates in
  both directions to the end.
• Most LAN use baseband signaling (e.g., Ethernet
  and FDDI)

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1. Data and Signals

• Broadband Technology
• A network technology that uses a large part of
  the electromagnetic spectrum to achieve higher
  throughput rates.
• Broadband refers to the use of analog signaling
• Usually broadband system employ frequency
  division multiplexing (FDM) to allow multiple,
  independent communications to proceed
  simultaneously over a single underlying medium.
• Much greater distances are possible with
  broadband compared to baseband. This is because
  the analog signals that carry the digital data
  can propagate greater distance before the noise
  and attenuation damage the data.

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1. Data and Signals

• Asynchronous Transmission
• Bits are sent one character at a time. (A
  character is in general 8 bits in length)
• Timing or synchronization must only be maintained
  within each character. The receiver has the
  opportunity to resynchronize at the beginning of
  each new character.
• Start-stop technique
• Idle state When no character is being
  transmitted the line between transmitter and
  receiver is in an idle state. The definition
  of idle is by convention, but typically is
  equivalent to the signaling element for binary 1.
• Start bit The beginning of a character is
  signaled by a start bit with a value of binary 0.
• Data bits
• Stop bit The last bit of the character is
  followed by a stop bit, which is a binary 1. A
  minimum length for the stop bit is specified and
  this is usually 1, 1.5 or 2 times the duration of
  an ordinary bit. No maximum value is specified,
  Since the stop bit is the same as the idle state.

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1. Data and Signals

• Example of an Asynchronous Transmission
• Given the facts that a steady stream of
  characters is sent, and the interval between
  characters is uniform and equal to the stop bit.
• Note
• Start bit 0
• Stop bit1
• ASCII character
• A 1000001
• B 0100001
• C 1100001
• The bit pattern of sending ASCII characters ABC
  (without parity bit) is
• 010000011001000011011000011...1111
• start bit(0) A (1000001) stop bit (1) start
  bit (0) B(0100001) stop bit (1) start bit
  (0) C(1100001)) stop bit (1)

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Asynchronous Communication
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1. Data and Signals

• Synchronous Transmission
• Blocks of characters or bits are transmitted
  without start and stop codes.
• To prevent timing drift between transmitter and
  receiver, their clocks must somehow be
  synchronized
• One possibility is to provide a separate clock
  line between transmitter and receiver
• Another possibility is to embed the clocking
  information in the data signal. For example for
  digital signals, this can be achieved with
  bi-phase encoding.
• Another level of synchronization is required, to
  allow the receiver to determine the beginning and
  end of a block of data.
• With character-oriented transmission, the frame
  begins with one or more synchronization
  characters. The synchronization character,
  usually called SYN, is a unique bit pattern that
  signals the receiver that this is the beginning
  of a block
• With bit-oriented transmission, a special bit
  pattern signals the beginning of a block In
  bit-oriented transmission, this preamble is eight
  bits long and is referred to as a flag.

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Synchronous Communication
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2. Advantages of Digital Transmission

• Digital transmission systems can operate with
  lower signal levels or with greater distances
  between repeaters than analog systems can. This
  factors translates into lower overall system cost
  and was the original motivation for the
  introduction of digital transmission.

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LG Figure 3.5 General Transmission system
Transmitter
Receiver
Communication channel
A transmission system make use of a physical
transmission medium or channel that allows the
propagation of energy in the form of pulse or
variations in voltage, current or light intensity
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2. Advantages of Digital Transmission

• Analog transmission
• Transmit a waveform, which is a function that
  varies continuously with time
• Digital transmission
• Transmit a given symbol that is selected from
  some finite set of possibilities
• For example, in binary digital transmission, the
  objective is to transmit either a 0 or a 1.

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Figure 3.6 Analog versus digital transmission

• (a) Analog transmission all details must be
  reproduced accurately

Received
Sent

• e.g. AM, FM, TV transmission

(b) Digital transmission only discrete levels
need to be reproduced
Received
Sent

• e.g digital telephone, CD Audio

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Figure 3.7 Typical long-distance link
Note To transmit over long distances, it is
necessary to introduce repeaters periodically to
regenerate the signal.
Transmission segment
Destination
Source
Repeater
Repeater
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2. Advantages of Digital Transmission

• Impact of distance on analog transmission
• Attenuation
• Different frequency components of the signal are
  attenuated differently
• In general, high frequency components are
  attenuated more than low-frequency components.
• Delay
• Different frequency components of a signal are
  delayed by different amounts
• Noise
• Analog repeater
• Attempts to eliminate the distortion caused by
  attenuation and delay by using equalizers

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LG Figure 3.8 An analog repeater
Recovered signal residual noise
Attenuated distorted signal noise
Amp.
Equalizer
Repeater
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LG Figure 3.9 A digital repeater

• Note
• Purpose is to determine with high probability
  the original binary stream
• Use an equalizer to compensate for the
  distortion
• The repeater does not need to completely
  regenerate the original shapes of the
  transmitted signal. It only needs to determine
  whether the original pulse was positive or
  negative.

Decision Circuit. Signal Regenerator
Amplifier Equalizer
Timing Recovery
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3. Fundamental Limits in Digital Transmission

• Using electric current to send bits and using
  electric voltage to encode bits
• The following figure illustrates how positive
  and negative voltage can be used to transmit bits
  across a wire. In this example, the sender
  applies a negative voltage to send a 1 bit or a
  positive voltage to send a 0 bits.

• Baud rate
• Bit rate is the number of bits per second. Baud
  rate is the number of signal units (pulses) per
  second that are required to represent those bits.
• Baud rate can be either less than, equal to, or
  greater than the bit rate.
• Each pulse can encode one or more bits of
  information (See multi-level pulses later)

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3. Fundamental Limits in Digital Transmission

• Limitations of real hardware The following
  figure illustrates the voltage emitted by a real
  device as it transmits a bit. In practice,
  voltage are often worse than this example.

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3. Fundamental Limits in Digital Transmission

• Hardware Bandwidth and the Transmission of Bits
• Each transmission system has a limited bandwidth,
  which is the maximum rate that the hardware can
  change a signal. If a sender attempts to
  transmit changes faster than the bandwidth, the
  hardware will not be able to keep up because it
  will not have sufficient time to complete one
  change before the sender attempts to make another
  . Thus some of the changes will be lost.

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3. Fundamental Limits in Digital Transmission

• Nyquist RateThe maximum data rate of a noiseless
  channel
• Nyquist derived an equation expressing the
  maximum data rate for a finite bandwidth
  noiseless channel
• If an arbitrary signal has been run through a
  low-pass filter of bandwidth W, the filtered
  signal can be completed reconstructed by making
  only 2W (exact) samples per second.
• Nyquist rate is based on the sampling theorem,
  which states If a signal f(t) is sampled at
  regular intervals of time and at a rate higher
  than twice the highest significant signal
  frequency, then the samples contain all the
  information of the original signal. The function
  f(t) may be reconstructed from these samples by
  the use of a low-pass filter.
• Sampling the line faster than 2W times per second
  is pointless because the higher frequency
  components that such sampling could recover have
  already been filtered out.
• A proof of the sampling theorem is based on the
  Fourier series and can be found in Data and
  Computer Communications by William Stallings

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3. Fundamental Limits in Digital Transmission

• Nyquist Rate
• For multilevel transmission pulses that can take
  on M 2m amplitude levels, the maximum bit rate
  is 2Wm bits/seconds
• R 2W pulses/second m bits/pulse
• 2Wm bits/second
• where
• R is bit rate in bits/seconds
• W is the bandwidth in Hz
• 2m M, M is the number of levels

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3. Fundamental Limits in Digital Transmission

• Multi-levels Pulse
• Two-levels pulse
• Binary information can be send by a pulse with
  amplitude A for a 1 bit and A for a 0 bit
• Bit rate is 2W bps
• Four-levels pulse
• With pulse taking on amplitude from the set
  -A,-A/3,A/3,A to transmit the pairs of bits
  00,01,10,11, then each pulse convey two bits of
  information. (Each increment of amplitude is
  equal to 2A divided by 3)
• Bit rate is 4W bps.
• Eight-levels pulse
• With pulse taking on amplitude from the set
  -A,-5A/7,-3A/7,A/7,A/7,3A/7,5A/7,A to
  transmit the bits 000,001,010,011,100,101,110,111
  , then each pulse convey three bits of
  information. (Each increment of amplitude is
  equal to 2A divided by 7)
• Bit rate is 6W bps.

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3. Fundamental Limits in Digital Transmission

• Nyquist Rate
• In the absence of noise, the bit rate can be
  increased without limit by increasing the number
  of signal levels M.
• Each increase in number of signal levels
• requires a reduction in the spacing between
  levels
• Increases the probability that noise will convert
  the transmitted signal levels into other signal
  levels.
• The presence of noise limits the reliability with
  which the receiver can correctly determine the
  information that was transmitted
• Increase the signal amplitude can decrease the
  effect of noise

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LG Figure 3.12 Signal-to-noise ratio
signal noise
signal
noise
High SNR
t
t
t
noise
signal noise
signal
Low SNR
t
t
t
Average Signal Power
SNR
Average Noise Power
SNR (dB) 10 log10 SNR
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3. Fundamental Limits in Digital Transmission

• Channel Capacity
• For a given bandwidth (W) and signal-to-noise
  ration (SNR), information can be transmitted up
  to C bits/seconds, with arbitrarily small
  probability of error by using sufficiently
  complex encoding systems
• It is not possible to transmit at a rate higher
  than C bits/seconds by any encoding system
  without a definite probability of error. In
  other words, it is not possible to transmit
  faster than C and have error free communication
• One of the most famous of all results of
  information theory is Shannons channel coding
  theorem. For a given channel there exists a code
  that will permit the error-free transmission
  across the channel at a rate R, provided R is
  less than C, the channel capacity is given by the
  following formula
• C Wlog2(1SNR) bits/seconds
• Note In equation above, SNR is not in decibel
  (dB)

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3. Fundamental Limits in Digital Transmission

• Channel Capacity
• Example
• When SNR approaches zero, then
• C Wlog2(1SNR) bits/seconds W log21 W0
  0
• When SNR is 1, then
• C Wlog2(1SNR) bits/seconds W log22 W1
  W
• Conversion between SNR and SNR(dB)
• SNR(dB) 10Log10 SNR
• SNR 10(SNR(dB)/10)
• Equation x 2y ? log2x log22y y
• Find minimum SNR for a particular C
• C Wlog2(1SNR) gt C/W log2(1SNR) gt
• 1SNR 2(C/W) gt SNR 2(C/W) -1

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3. Fundamental Limits in Digital Transmission

• Channel Capacity
• Example For a channel of 3000 Hz bandwidth, and
  a signal-to-noise (SNR) of 30 dB, the Shannons
  channel capacity is
• SNR 10(SNR(dB)/10) 10(30/10) 103 1000
• C Wlog2(1SNR) bits/seconds
• 3000 log2(11000) 3000
  (log101001)/(log102)
• 3000 (3.0004)/(0.30103) 29901.3
  bits/seconds
• C is less than 30 K bits/seconds