1. Rudra Dutta CSC 401 - Fall 2011, Section 001
Physical Layer
Rudra Dutta
CSC Fall 2011, Section 001

2. Context Lowest of OSI layers Provides a bit pipe
More communications than networking
We want to understand:
General techniques
Descriptive
Theoretical results
Analytical, problem solving
Copyright Fall 2011, Rudra Dutta, NCSU

3. Communication Links Various technologies for physical communication
Copper wire, coax, fiber, radio, satellites, …
Single underlying phenomenon - EM waves
One way to utilize the phenomenon - guide
Copper, glass
Another way – no guide
Free space (“wireless cable”)
Radio, optical
(Smoke signal? Semaphore? Magnetic tapes? Carrier Pigeons ?)
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4. 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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5. Digital or Analog ? Digital – concept EM waves – analog by definition
010100…
Digital – concept
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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6. Propagation Media Guided Unguided Twisted pair Coax cable
Optical fiber
Unguided
Radio (semi-guided follow curvature of earth)
Radio bounced off ionosphere
Fiberless optical (wireless optical)
Communication satellites
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7. Communication in the EM Spectrum
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8. Modulation A “carrier” wave exists on the medium
Own amplitude, frequency, phase
Base energy pattern – no information
Analog, of course
A “signal” needs to be transmitted
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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9. Injection Baseband Broadband No carrier, modulation
State of the medium (voltage) is made to follow signal one-to-one
Uses “entire” medium
Broadband
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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10. Synchronous vs. Asynchronous
Various use of these terms
Very multiply defined terms
Can be used for traffic
ITU-T and CCITT have different definitions
Others such as FDDI possible
In this transmission context
With clock - asynchronous
Can fall out of step - long string of zeros
Synchronous - clock not needed
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11. Synchronous Baseband Transmission
“Self-synchronizing” codes
Provide guaranteed transitions in clock ticks
Rate suffers
Manchester
Transitions, not states, indicate bits
Many others
NRZI - Transitions indicate 1’s (needs line code)
MLT-3 - Alternate 1’s are high and low (needs line code)
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12. Broadband injection Amplitude, Frequency, or Phase may be modulated
“Shift keying”
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13. BPSK modulation PSK has excellent protection against noise
Information is contained within phase
Noise mainly affects carrier amplitude
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14. QPSK Modulation, QAM
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15. Multiplexing
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
Frequency division
Time division
Combinations thereof
Code division – new concept
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16. Frequency Division Multiplexing
(a) The original bandwidths
(b) The bandwidths raised in frequency
(b) The multiplexed channel
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17. Wavelength Division Multiplexing
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18. Time Division Multiplexing
The T1 carrier (1.544 Mbps)
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19. GSM – A Combined Approach
GSM uses 124 frequency channels, each of which uses an eight-slot TDM system
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20. CDMA – A New Approach Combines multiplexing and collision issues
New approach lies in treating collisions - may extract some data
Multiplexing is more like FDM
Binary “chip” sequences assigned to stations
May appear that bit rate increase should not result - in fact does
Power control an essential part
We discuss later (in MAC)
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21. The Issue of Bitrate Consider simple AM (ASK)00 01 10 11 1
Consider simple AM (ASK)
Transmit one of two distinct amplitudes (voltages)  transmission of one bit
How soon after can we transmit another bit?
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
Why not transmit one of four distinct amplitudes?
Why not more?  No limit to bit rate
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22. Channel Characteristics
Channel modifies the EM wave
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23. Phenomena Hindering Transmission
Interference with energy (pattern)
Attenuation (entropy loss)
Distortion (variable delay of different energy packets)
Dispersion
Noise (unpredictable)
All but noise can be guarded against
With the ideal infinite data transfer rate
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24. A Little Communication Theory
The road to EM transmission:
Fourier: Harmonic analysis
Nyquist: Sampling theorem – bit rate
Shannon: Bit rate in presence of noise
Briefly,
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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25. Bandwidth-Limited Signals
(a) A binary signal and its root-mean-square Fourier amplitudes, (b-c) successive approximations
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26. Bandwidth-Limited Signals (2)
(d) – (e) Successive approximations to the original signal
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27. Sampling – Nyquist’s Theorem
Twice the highest frequency  no reconstruction loss
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28. Nyquist’s Result – Intuitive View
Fitting a sinusoid
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”
Naturally introduced by device characteristics
Medium carries all frequencies between a lowest and highest frequencies (“frequency band”)
Hence “band” “width”
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29. Bandwidth limited Bit rate
Nyquist’s theorem
Maximum bit rate = 2H log2 V bits/sec
H = bandwidth
V = number of discrete states
Shannon’s theorem
Maximum bit rate = H log2 (1 + S/N) bits/sec
Introduces signal-noise ratio
Insight: random characteristic limits bit rate
Note on application
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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30. Examples
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.
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 (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 * * log22 = 12 Mbps. Thus this is the maximum bitrate that will be achieved by a binary signal.
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31. Comparing Results Both results give bitrates, but Nyquist’s theorem
With different assumptions and input
Nyquist’s theorem
Bit rate IF exactly V states are successfully used
Mo-Dem equipment already decided
Noise must allow V states
Often stated as perfect channel assumption
Shannon’s result
Estimation of what value of V will be successful
Noise level decides, so need noise level as input
Either might be larger, depending on input
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32. What Have We Learned?
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
Copyright Fall 2011, Rudra Dutta, NCSU