1. EC 723 Satellite Communication Systems
Mohamed Khedr

2. Syllabus Tentatively Week 1 Overview Week 2
Orbits and constellations: GEO, MEO and LEO
Week 3
Satellite space segment, Propagation and satellite links , channel modelling
Week 4
Satellite Communications Techniques
Week 5
Satellite Communications Techniques II
Week 6
Satellite Communications Techniques III
Satellite error correction Techniques
Week 7
Multiple Access I
Week 8
Multiple access II
Week 9
Satellite in networks I, INTELSAT systems , VSAT networks, GPS
Week 10
GEO, MEO and LEO mobile communications
INMARSAT systems, Iridium , Globalstar, Odyssey
Week 11
Presentations
Week 12
Week 13
Week 14
Week 15
Tentatively

3. Frequency Shift Keying
Two signals are used to convey information
In principle, the transmitted signal appears as 2 sinx/x functions at carrier frequencies
Each of the two states represents a single bit of information
Each state persists for a single bit period and then may be replaced either state
BER is: 2x BPSK BER for coherent for non-coherent
Constant Modulus =>

4. Frequency Shift Keying

5. Other Modulations (cont.)
M-ary PSK
PSK with 2n states where n>2
Incr. spectral eff. - (More bits per Hertz)
Degraded BER compared to BPSK or QPSK
QAM - Quadrature Amplitude Modulation
Not constant envelope
Allows higher spectral eff.

6. M-ary PSK

7. M-ary QAM

8. Other Modulations OQPSK MSK QPSK
One of the bit streams delayed by Tb/2
Same BER performance as QPSK
MSK
QPSK - also constant envelope, continuous phase FSK
1/2-cycle sine symbol rather than rectangular

9. Noncoherent receivers. (a) Quadrature receiver using correlators
Noncoherent receivers. (a) Quadrature receiver using correlators. (b) Quadrature receiver using matched filters. (c) Noncoherent matched filter.

10. Output of matched filter for a rectangular RF wave: (a) q  0, and (b) q  180 degrees.

11. Noncoherent receiver for the detection of binary FSK signals.

12. Factors that Influence Choice of Digital Modulation Techniques
A desired modulation scheme
Provides low bit-error rates at low SNRs
Power efficiency
Performs well in multipath and fading conditions
Occupies minimum RF channel bandwidth
Bandwidth efficiency
Is easy and cost-effective to implement
Depending on the demands of a particular system or application, tradeoffs are made when selecting a digital modulation scheme.

13. Power Efficiency of Modulation
Power efficiency is the ability of the modulation technique to preserve fidelity of the message at low power levels.
Usually in order to obtain good fidelity, the signal power needs to be increased.
Tradeoff between fidelity and signal power
Power efficiency describes how efficient this tradeoff is made
Eb: signal energy per bit
N0: noise power spectral density
PER: probability of error

14. Bandwidth Efficiency of Modulation
Ability of a modulation scheme to accommodate data within a limited bandwidth.
Bandwidth efficiency reflect how efficiently the allocated bandwidth is utilized
R: the data rate (bps)
B: bandwidth occupied by the modulated RF signal

15. Shannon’s Bound
There is a fundamental upper bound on achievable bandwidth efficiency.
Shannon’s theorem gives the relationship between the channel
bandwidth and the maximum data rate that can be transmitted over this
channel considering also the noise present in the channel.
Shannon’s Theorem
C: channel capacity (maximum data-rate) (bps)
B: RF bandwidth S/N: signal-to-noise ratio (no unit)

16. Shannon Bound
1948 Shannon demonstrated that, with proper coding a channel capacity of
Required channel quality
for error free communications
=>we’re doing much worse

17. Tradeoff between BW Efficiency and Power Efficiency
There is a tradeoff between bandwidth efficiency and power efficiency
Adding error control codes
Improves the power efficiency
Reduces the requires received power for a particular bit error rate
Decreases the bandwidth efficiency
Increases the bandwidth occupancy
M-ary keying modulation
Increases the bandwidth efficiency
Decreases the power efficiency
More power is requires at the receiver

18. Example:
SNR for a wireless channel is 30dB and RF bandwidth is 200kHz. Compute the theoretical maximum data rate that can be transmitted over this channel?
Answer:

19. Modulation Schemes Error Performance

20. M-ary PSK Error Performance

21. Operation Point Comparison

22. Union bound Union bound
GMU - TCOM Spring 2001
Union bound
Class: Feb
Union bound
The probability of a finite union of events is upper bounded
by the sum of the probabilities of the individual events.
Let denote that the observation vector is closer to the symbol vector than , when is transmitted.
depends only on and
Applying Union bounds yields
Lecture 5
(C) Leila Z. Ribeiro, 2001

23. Example of union bound Union bound: 2006-02-07 Lecture 5
GMU - TCOM Spring 2001
Example of union bound
Class: Feb
Union bound:
Lecture 5
(C) Leila Z. Ribeiro, 2001

24. Upper bound based on minimum distance
GMU - TCOM Spring 2001
Upper bound based on minimum distance
Class: Feb
Minimum distance in the signal space:
Lecture 5
(C) Leila Z. Ribeiro, 2001

25. Example of upper bound on av. Symbol error prob. based on union bound
GMU - TCOM Spring 2001
Example of upper bound on av. Symbol error prob. based on union bound
Class: Feb
Lecture 5
(C) Leila Z. Ribeiro, 2001

26. Summary of Useful Formulas

27. Summary of Digital Communications -1
Legend of variables mentioned in this section:
M = modulation size. (Ex: 2, 4, 16, 64)
Bw = Bandwidth in Hertz
 = Roll-off factor (from 0 to 1)
Gc = Coding Gain (convert from dB to linear to use in formulas)
Ov = Channel Overhead (convert from % to fraction : 0 to1)
BER = Bit Error Rate

28. Summary of Digital Communications - 2
Bits per Symbol:
Symbol Rate [symbol/second]:
Gross Bit Rate [bps]:
Net Data Rate [bps]:

29. BER Calculation as a Function of Modulation Scheme and Eb/No Available
Equations given on next slide are used to calculate the bit error rate (BER) given the bit energy by spectral noise ratio (Eb/No) as input.
These functions are used in their direct form for the bit error rate calculations. Excel and some scientific calculators provide the solution for the “erfc” function.
The formulas provided can be inverted by numerical methods to obtain the Eb/No required as a function of the BER.
Also possible to draw the graphic and obtain the “inverse” by graphical inspection.

30. BER Calculation as a Function of Modulation Scheme and Eb/No Available - 2

31. Maximum Likelihood (ML) Detection: Concepts

32. Likelihood Principle Experiment: The ball is black.
Pick Urn A or Urn B at random
Select a ball from that Urn.
The ball is black.
What is the probability that the selected Urn is A?

33. Likelihood Principle (Contd)
Write out what you know!
P(Black | UrnA) = 1/3
P(Black | UrnB) = 2/3
P(Urn A) = P(Urn B) = 1/2
We want P(Urn A | Black).
Gut feeling: Urn B is more likely than Urn A (given that the ball is black). But by how much?
This is an inverse probability problem.
Make sure you understand the inverse nature of the conditional probabilities!
Solution technique: Use Bayes Theorem.

34. Likelihood Principle (Contd)
Bayes manipulations:
P(Urn A | Black) =
P(Urn A and Black) /P(Black)
Decompose the numerator and denomenator in terms of the probabilities we know.
P(Urn A and Black) = P(Black | UrnA)*P(Urn A)
P(Black) = P(Black| Urn A)*P(Urn A) + P(Black| UrnB)*P(UrnB)
We know all these values Plug in and crank.
P(Urn A and Black) = 1/3 * 1/2
P(Black) = 1/3 * 1/2 + 2/3 * 1/2 = 1/2
P(Urn A and Black) /P(Black) = 1/3 = 0.333
Notice that it matches our gut feeling that Urn A is less likely, once we have seen black.
The information that the ball is black has CHANGED !
From P(Urn A) = 0.5 to P(Urn A | Black) = 0.333

35. Likelihood Principle Way of thinking… Hypotheses: Urn A or Urn B ?
Observation: “Black”
Prior probabilities: P(Urn A) and P(Urn B)
Likelihood of Black given choice of Urn: {aka forward probability}
P(Black | Urn A) and P(Black | Urn B)
Posterior Probability: of each hypothesis given evidence
P(Urn A | Black) {aka inverse probability}
Likelihood Principle (informal): All inferences depend ONLY on
The likelihoods P(Black | Urn A) and P(Black | Urn B), and
The priors P(Urn A) and P(Urn B)
Result is a probability (or distribution) model over the space of possible hypotheses.

36. Maximum Likelihood (intuition)
Recall:
P(Urn A | Black) = P(Urn A and Black) /P(Black) =
P(Black | UrnA)*P(Urn A) / P(Black)
P(Urn? | Black) is maximized when P(Black | Urn?) is maximized.
Maximization over the hypotheses space (Urn A or Urn B)
P(Black | Urn?) = “likelihood”
=> “Maximum Likelihood” approach to maximizing posterior probability

37. Maximum Likelihood (ML): mechanics
Independent Observations (like Black): X1, …, Xn
Hypothesis 
Likelihood Function: L() = P(X1, …, Xn | ) = i P(Xi | )
{Independence => multiply individual likelihoods}
Log Likelihood LL() = i log P(Xi | )
Maximum likelihood: by taking derivative and setting to zero and solving for 
Maximum A Posteriori (MAP): if non-uniform prior probabilities/distributions
Optimization function P

38. OFDM GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001
(C) Leila Z. Ribeiro, 2001

39. Motivation High bit-rate wireless applications in a multipath radio
GMU - TCOM Spring 2001
Class: Feb
Motivation
High bit-rate wireless applications in a multipath radio
environment.
OFDM can enable such applications without a high
complexity receiver.
OFDM is part of WLAN, DVB, and BWA standards
and is a strong candidate for some of the 4G wireless
technologies.
(C) Leila Z. Ribeiro, 2001

40. What is OFDM? Modulation technique Requires channel coding
Solves multipath problems
Transmitter:
I/Q RF
Source coding
Channel coding / interleaving
OFDM modulation
I/Q-mod., up-
converter
Info
Source
e.g. Audio
0110
OFDM de-modulation
Source decoding
Down-converter, I/Q-demod.
I/Q RF
Decoding / deinter-leaving
Receiver:
Radio-
channel
Info
Sink f
PSD * f
PSD fc
-fc

41. Multipath Transmission
GMU - TCOM Spring 2001
Class: Feb
Multipath Transmission
Fading due to constructive and destructive addition of
multipath signals.
Channel delay spread can cause ISI.
Flat fading occurs when the symbol period is large compared
to the delay spread.
Frequency selective fading and ISI go together.
(C) Leila Z. Ribeiro, 2001

42. Multipath Propagation
GMU - TCOM Spring 2001
Multipath Propagation
Class: Feb
Reflections from walls, etc.
Time dispersive channel
Impulse response:
Problem with high rate data transmission:
inter-symbol-interference t
[ns] p (
) (PDP)
Multipath Radio Channel
(C) Leila Z. Ribeiro, 2001

43. Delay Spread Power delay profile conveys the multipath delay spread
GMU - TCOM Spring 2001
Class: Feb
Delay Spread
Power delay profile conveys the multipath delay spread
effects of the channel.
RMS delay spread quantifies the severity of the ISI
phenomenon.
The ratio of RMS delay spread to the data symbol period
determines the severity of the ISI.
. Figure of a typical PDP used in WLAN say Channel A should be given along with the rms delay spread, this figure is available in the electronic format
. Give an indication of the severity of the ISI in terms of the number of data symbols to the rms/max. delay spread .. Take the WLAN example
(C) Leila Z. Ribeiro, 2001

44. Inter-Symbol-Interference
Transmitted signal:
Received Signals:
Line-of-sight:
Reflected:
The symbols add up on the channel
Delays
 Distortion!
Multipath Radio Channel

45. Concept of parallel transmission (1)
GMU - TCOM Spring 2001
Concept of parallel transmission (1)
Class: Feb
Channel impulse
response
Time
1 Channel (serial)
2 Channels
Channels are transmitted
at different frequencies
(sub-carriers)
8 Channels
In practice: 50 … 8000
Channels (sub-carriers)
OFDM Technology
(C) Leila Z. Ribeiro, 2001

46. The Frequency-Selective Radio Channel
GMU - TCOM Spring 2001
Class: Feb
The Frequency-Selective Radio Channel
-10 -5 5 10 15 20
Frequency
Power response [dB]
Interference of reflected (and LOS) radio waves
Frequency-dependent fading
Multipath Radio Channel
(C) Leila Z. Ribeiro, 2001

47. Concept of parallel transmission (2)
GMU - TCOM Spring 2001
Class: Feb
Concept of parallel transmission (2)
Channel impulse
response
Channel
transfer function
Frequency
Time
Signal is
“broadband”
1 Channel (serial)
Frequency
2 Channels
Frequency
8 Channels
Frequency
Channels are
“narrowband”
OFDM Technology
(C) Leila Z. Ribeiro, 2001

48. Concept of an OFDM signal
Ch.1
Ch.2
Ch.3
Ch.4
Ch.5
Ch.6
Ch.7
Ch.8
Ch.9
Ch.10
Conventional multicarrier techniques
frequency
Ch.2
Ch.4
Ch.6
Ch.8
Ch.10
Ch.1
Ch.3
Ch.5
Ch.7
Ch.9
Saving of bandwidth
50% bandwidth saving
Orthogonal multicarrier techniques
frequency
Implementation and System Model

49. A Solution for ISI channels
GMU - TCOM Spring 2001
Class: Feb
A Solution for ISI channels
Conversion of a high-data rate stream into several low-rate
streams.
Parallel streams are modulated onto orthogonal carriers.
Data symbols modulated on these carriers can be recovered
without mutual interference.
Overlap of the modulated carriers in the frequency domain -
different from FDM.
- figure difference between OFDM and FDM would be useful here
(C) Leila Z. Ribeiro, 2001

50. OFDM OFDM is a multicarrier block transmission system.
GMU - TCOM Spring 2001
Class: Feb
OFDM
OFDM is a multicarrier block transmission system.
Block of ‘N’ symbols are grouped and sent parallely.
No interference among the data symbols
sent in a block.
(C) Leila Z. Ribeiro, 2001

51. OFDM Mathematics t º [ 0,Tos] Orthogonality Condition In our case
For p ¹ q Where fk=k/T

52. Transmitted Spectrum GMU - TCOM 507 - Spring 2001 Class: Feb-22-2001
(C) Leila Z. Ribeiro, 2001

53. Spectrum of the modulated data symbols
Rectangular Window of duration T0
Has a sinc-spectrum with zeros at 1/ T0
Other carriers are put in these zeros
 sub-carriers are orthogonal T0
Magnitude
Frequency
N sub-carriers:
resembles
IDFT!

54. OFDM terminology
Orthogonal carriers referred to as subcarriers {fi,i=0,....N-1}.
OFDM symbol period {Tos=N x Ts}.
Subcarrier spacing Df = 1/Tos.

55. OFDM and FFT Samples of the multicarrier signal can be obtained using
GMU - TCOM Spring 2001
Class: Feb
OFDM and FFT
Samples of the multicarrier signal can be obtained using
the IFFT of the data symbols - a key issue.
FFT can be used at the receiver to obtain the data symbols.
No need for ‘N’ oscillators,filters etc.
Popularity of OFDM is due to the use of IFFT/FFT which
have efficient implementations.
(C) Leila Z. Ribeiro, 2001

56. OFDM Signal
t º [ 0,Tos]
Otherwise
K=0, N-1

57. By sampling the low pass equivalent signal at a rate N times
higher than the OFDM symbol rate 1/Tos, OFDM frame
can be expressed as:
m = 0....N-1

58. Interpretation of IFFT&FFT
IFFT at the transmitter & FFT at the receiver
Data symbols modulate the spectrum and the time domain symbols are obtained using the IFFT.
Time domain symbols are then sent on the channel.
FFT at the receiver to obtain the data.

59. Interference between OFDM Symbols
GMU - TCOM Spring 2001
Class: Feb
Interference between OFDM Symbols
Transmitted Signal
OS1
OS2
OS3
Due to delay spread ISI occurs
Delay Spread
IOSI
Solution could be guard interval between OFDM symbols
(C) Leila Z. Ribeiro, 2001

60. Cyclic Prefix Zeros used in the guard time can alleviate interference
between OFDM symbols (IOSI problem).
Orthogonality of carriers is lost when multipath channels
are involved.
Cyclic prefix can restore the orthogonality.

61. Cyclic Prefix Convert a linear convolution channel into a circular
This restores the orthogonality at the receiver.
Energy is wasted in the cyclic prefix samples.

62. Cyclic Prefix Illustration
GMU - TCOM Spring 2001
Class: Feb
Cyclic Prefix Illustration Tg
Tos
OS 1
OS 2
Cyclic Prefix
OS1,OS2 - OFDM Symbols
Tg Guard Time Interval
Ts Data Symbol Period
Tos OFDM Symbol Period - N * Ts
(C) Leila Z. Ribeiro, 2001

63. Guard interval (2) - Cyclic extension

64. Design of an OFDM System
Nr. of
carriers
Data rate;
modulation
order
Channel
impulse
response
Guard
interval
length
x(4 … 10)
FFT
symbol
length
Other constraints:
Nr. of carriers should match FFT size
and data packet length
considering coding and modulation schemes
Channel
Parameters
are needed
Introduction

65. Spectral Shaping by Windowing
OFDM System Design

66. OFDM Symbol Configuration
Not all FFT-points can be used for data carriers
Lowpass filters for AD- and DA-conversion
oversampling required
Design of an OFDM System

67. Advantages of OFDM Solves the multipath-propagation problem
Simple equalization at receiver
Computationally efficient
For broadband systems more efficient than SC
Supports several multiple access schemes
TDMA, FDMA, MC-CDMA, etc.
Supports various modulation schemes
Adaptability to SNR of sub-carriers is possible
Elegant framework for MIMO-systems
All interference among symbols is removed

68. Problems of OFDM (Research Topics)
GMU - TCOM Spring 2001
Problems of OFDM (Research Topics)
Class: Feb 20 40 60 80
100
120
140
160
180
200
-0.2
-0.1
0.1
0.2
time domain signal (baseband)
sample nr.
imaginary
real
Synchronization issues:
Time synchronization
Find start of symbols
Frequency synchr.
Find sub-carrier positions
Non-constant power envelope
Linear amplifiers needed
Channel estimation:
To retrieve data
Channel is time-variant
OFDM Technology
(C) Leila Z. Ribeiro, 2001

69. OFDM Transmitter Input Symbols X0 x0 Parallel to Serial and add CP
GMU - TCOM Spring 2001
Class: Feb
OFDM Transmitter X0 x0
Parallel to
Serial
and
add CP
Serial to
Parallel
Input
Symbols
Add CP
IFFT
XN-1
xN-1
RF Section
DAC
Windowing
(C) Leila Z. Ribeiro, 2001

70. OFDM Receiver x0 X0 ADC and Remove CP Parallel to Serial and Decoder
GMU - TCOM Spring 2001
Class: Feb
OFDM Receiver x0 X0
ADC
and
Remove CP
Parallel
to Serial
and
Decoder
Serial to
Parallel
Output
Symbols
FFT
xN-1
XN-1
(C) Leila Z. Ribeiro, 2001

71. Synchronization Timing and frequency offset can influence performance.
Frequency offset can influence orthogonality of subcarriers.
Loss of orthogonality leads to Inter Carrier Interference.

72. Peak to Average Ratio
Multicarrier signals have high PAR as compared to single
carrier systems.
PAR increases with the number of subcarriers.
Affects power amplifier design and usage.

73. Peak to Average Power Ratio