Transcript Physical - Rudra Dutta

Physical Layer
Rudra Dutta
CSC 401 - Fall 2011, Section 001
Context
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Lowest of OSI layers
 Provides a bit pipe
 More communications than networking
 We want to understand:
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General techniques
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Descriptive
Theoretical results
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Analytical, problem solving
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Communication Links
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Various technologies for physical communication
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Copper wire, coax, fiber, radio, satellites, …
Single underlying phenomenon - EM waves
One way to utilize the phenomenon - guide
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Copper, glass
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Another way – no guide
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Free space (“wireless cable”)
– Radio, optical
(Smoke signal? Semaphore? Magnetic tapes? Carrier Pigeons ?)
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EM Waves
Energy can carry information
More correctly, distribution of energy
EM waves carry energy, hence information
Amplitude, frequency, phase
Modifications (“modulations”) of these carry information
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Digital or Analog ?
010100…
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Digital – concept
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Information can be analog or digital
EM waves – analog by definition
 Analog EM signal can be made to transfer digital data
 Thus we could (and usually do) have:
 “Digital interpretation of analog signal representing
digital representation of analog data”
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Propagation Media
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Guided
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Twisted pair
Coax cable
Optical fiber
Unguided
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Radio (semi-guided follow curvature of earth)
– Radio bounced off ionosphere
– Fiberless optical (wireless optical)
– Communication satellites
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Communication in the EM Spectrum
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Modulation
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A “carrier” wave exists on the medium
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A “signal” needs to be transmitted
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Own amplitude, frequency, phase
Base energy pattern – no information
Analog, of course
Time varying; analog, or digital
The value of the signal from instant to instant is
used to change the energy pattern of the carrier
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Injection
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Baseband
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No carrier, modulation
State of the medium (voltage) is made to follow
signal one-to-one
Uses “entire” medium
Broadband
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Modulation of a carrier
– Carriers at different frequencies can carry different
signals
– Sinusoidal advantages – remember harmonic
analysis
– Natural frequencies of transmission
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Synchronous vs. Asynchronous
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Various use of these terms
 Very multiply defined terms
 Can be used for traffic
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ITU-T and CCITT have different definitions
– Others such as FDDI possible
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In this transmission context
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With clock - asynchronous
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Can fall out of step - long string of zeros
Synchronous - clock not needed
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Synchronous Baseband Transmission
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“Self-synchronizing” codes
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Manchester
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Provide guaranteed transitions in clock ticks
Rate suffers
Transitions, not states, indicate bits
Many others
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NRZI - Transitions indicate 1’s (needs line code)
MLT-3 - Alternate 1’s are high and low (needs line code)
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Broadband injection
Amplitude, Frequency, or Phase may be modulated
“Shift keying”
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BPSK modulation
• PSK has excellent protection against noise
• Information is contained within phase
• Noise mainly affects carrier amplitude
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QPSK Modulation, QAM
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Multiplexing
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Techniques to employ same medium for
multiple transmissions
 Requirement: over same reasonably short time,
each transmission should receive some share of
medium capability
 Two main methods
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Frequency division
Time division
Combinations thereof
Code division – new concept
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Frequency Division Multiplexing
(a) The original bandwidths
(b) The bandwidths raised in frequency
(b) The multiplexed channel
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Wavelength Division Multiplexing
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Time Division Multiplexing
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The T1 carrier (1.544 Mbps)
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GSM – A Combined Approach
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GSM uses 124 frequency channels, each of
which uses an eight-slot TDM system
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CDMA – A New Approach
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Combines multiplexing and
collision issues
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New approach lies in treating
collisions - may extract some data
– Multiplexing is more like FDM
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Binary “chip” sequences assigned
to stations
May appear that bit rate increase
should not result - in fact does
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Power control an essential part
– We discuss later (in MAC)
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The Issue of Bitrate
00
1 01
0
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Transmit one of two distinct amplitudes (voltages) 
transmission of one bit
How soon after can we transmit another bit?
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Consider simple AM (ASK)
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How fast can transmitter change its state?
How fast can receiver recognize line state?
Appears to limit bit rate, but -
Does not have to be just two states
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Why not transmit one of four distinct amplitudes?
Why not more?  No limit to bit rate
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Channel Characteristics
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Channel modifies the EM wave
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Phenomena Hindering Transmission
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Interference with energy (pattern)
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Attenuation (entropy loss)
Distortion (variable delay of different energy packets)
Dispersion
Noise (unpredictable)
All but noise can be guarded against
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With the ideal infinite data transfer rate
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A Little Communication Theory
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The road to EM transmission:
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Fourier: Harmonic analysis
Nyquist: Sampling theorem – bit rate
Shannon: Bit rate in presence of noise
Briefly,
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Most signals can be represented by sinusoid
combinations
– Discrete time sampling can reconstruct signals
– Noiseless channel has limited maximum bit rate
– Noise reduces maximum bit rate
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Bandwidth-Limited Signals
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(a) A binary signal and its root-mean-square Fourier
amplitudes, (b-c) successive approximations
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Bandwidth-Limited Signals (2)
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(d) – (e) Successive approximations to the
original signal
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Sampling – Nyquist’s Theorem
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Twice the highest frequency  no
reconstruction loss
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Nyquist’s Result – Intuitive View
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Fitting a sinusoid
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Low-rate sampling  wrong sinusoid
Half-rate sampling  wrong sinusoid
Full-rate sampling  still could be wrong
Double rate  no possibility of wrong sinusoid
“Highest frequency”
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Naturally introduced by device characteristics
Medium carries all frequencies between a lowest
and highest frequencies (“frequency band”)
Hence “band” “width”
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Bandwidth limited Bit rate
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Nyquist’s theorem
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Maximum bit rate = 2H log2 V bits/sec
H = bandwidth
V = number of discrete states
Shannon’s theorem
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Maximum bit rate = H log2 (1 + S/N) bits/sec
Introduces signal-noise ratio
Insight: random characteristic limits bit rate
Note on application
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SNR in Shannon’s theorem - ratio of power content (PS/PN)
Usual unit of SNR - dB, a logarithmic unit
dB = 10 log10 (PS/PN)
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Examples
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A digital signal is sent over a 7.5-kHz channel whose signal-to-noise ratio is
20 dB. What is the maximum achievable data rate?
 Since 20 dB is the same as 100:1 (because 20 = 10 log10(100/1)), we apply
Shannon’s theorem to obtain 7500 (log2101) = 50 Kbps.
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A binary signal is sent over a 6 MHz channel with SNR 30 dB. What data
rate will be achieved?
 Again, the theoretically maximum bitrate of the channel is available as
6000000 (log21001) = 59.8 Mbps. But in this case, we are already told that
the signal is binary, that is only two discrete states of the medium can be
used. We may not be able to utilize the full SNR of the medium with only
two states; to check, we must apply Nyquist’s theorem with V = 2. Indeed,
we get 2 * 6000000 * log22 = 12 Mbps. Thus this is the maximum bitrate
that will be achieved by a binary signal.
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Comparing Results
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Both results give bitrates, but
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With different assumptions and input
Nyquist’s theorem
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Bit rate IF exactly V states are successfully used
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Noise must allow V states
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Often stated as perfect channel assumption
Shannon’s result
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Estimation of what value of V will be successful
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Mo-Dem equipment already decided
Noise level decides, so need noise level as input
Either might be larger, depending on input
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What Have We Learned?
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EM communication links provide bit pipes –
lowest layer of networking
Various transmission methodologies
Theoretical results providing channel bit rates
At higher layers, bit rate is what we are primarily
interested in
Validation of layering concept
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