1. Wireless Communications Systems
Dr. Jose A. Santos

2. Course Objectives and Learning Outcomes
The course aim is to “Introduce the theory and practice of analogue and digital wireless communications systems and to enable a clear understanding of the “state of the art” of wireless technology.

3. Learning Outcomes
Upon the successful completion of this module a successful student will:
Be equipped with a sound knowledge of modern wireless communications technologies
Comprehend the techniques of spread spectrum and be able to explain its pervasiveness in wireless technologies.

4. Learning Outcomes
Understand, the design of a modern wireless communication system and be capable of analysing such systems
satellite communications,
cellular wireless,
cordless systems and
wireless local loop.

5. Learning Outcomes
Understand different Wireless LANs technologies and Identify key elements that characterize the protocol architecture of such technologies.
Have gained practical experience in the implementation of wireless technologies and systems in MATLAB and be capable of performing experimental tests on these systems, analysing the results

6. Course Contents Subject Area 1: Transmission Fundamentals & Principles
Basic Mathematical Communication Concepts – The Decibel (Week 1)
Time Characterization of Signals (Week 1)
Frequency Characterization of Signals (Week 1)

7. Course Contents Subject Area 1: Transmission Fundamentals & Principles
The Fourier Transform and Its Properties (Week 1)
Analogue and Digital Data Transmission (Week 2)
Channel Capacity, Data Rate, Bandwidth and Transmission Media (Week 2)

8. Course Contents Subject Area 2: Wireless Communications Technologies
Antennas and Propagation (Week 3)
Signal Encoding Techniques (Week 4)
Spread Spectrum Techniques (Week 5)
Coding and Error Control in Wireless Transmissions (Week 6)

9. Course Content Subject Area 3: Wireless Networking
Satellite Communications (Week 7)
Cellular Wireless Networks (Week 8 & 9)
Cordless Systems (Week 10)
Wireless Local Loop (Week 10)
Mobile IP and Wireless Access Protocol (Week 11)

10. Course Content Subject Area 4: Wireless LANs
Wireless LAN Technologies (Week 12)
IEEE Wireless LAN Standards (Mandatory Reading)
Bluetooth (Mandatory Reading)

11. Course Content Subject Area 5: MATLAB Practicals
Introduction to MATLAB, Fourier Analysis & Power Spectrum Generation (Week 3-4)
Functions in MATLAB, Modulation Techniques (AM, FM, ASK, FSK) (Week 5-7)
Introduction to Simulink, Basic Communications Models, Error Control, Modulation Systems. (Week 8)
Laboratory Exam (Week 12)

12. Teaching Schedule & Evaluation
End of year Examination (75%)
Coursework (25%)
Literature Review Paper (50%) Week 5
Essay(25%) Week 9
Laboratory Exam (25%) Week 12
For Details on CW and Exam consult the CW Handout Document on the module website.

13. Course Reading List Essential: Additional Resources:
Stallings, W. “Wireless Communications and Networks,” Prentice Hall and 2nd Ed
Additional Resources:
Mark, J and Zhuang W. “Wireless Communications and Networking” Prentice Hall. 2003
Shankar, P.M. “Introduction to Wireless Systems”, John Wiley & Sons Inc
Proakis, J. “Communication Systems Engineering” 2nd Ed. Prentice Hall, 2002.
Haykin, S. and Moher, M. “Modern Wireless Communications,” International Ed. Prentice Hall, 2005.

14. Availability and Contact
Module Delivery
Class Structures:
Theory Class 2 Hours (Every week)
Tutorials 1 Hours (Selected weeks)
Labs (3 Practicals in 11 Weeks)
Availability and Contact
Dr. Jose A. Santos
Room MG121E

15. Introduction to Wireless Systems

16. Class 1 Contents - Introduction
Introduction & Review of Mathematical Concepts
Wireless and the OSI Model
The Decibel Concept
dB & dBm – Application to logarithmic formulas
Signal Concepts
Time Domain Signals
Frequency Domain Concepts

17. Class Contents Introduction to Fourier Analysis of Signals
The Fourier Transform Theorem
The Fourier Series Representation

18. Wireless & Open System Interconnection Model
Wireless is only one component of the complex systems that allows seamless communications world wide.
Wireless is concerned with 3 of the 7 layers of the OSI reference model:

19. Wireless & Open System Interconnection Model
Physical Layer: Physical Mechanisms for transmission of binary digits. (Modulation, Demodulation & Transmission Medium Issues).
Data-Link Layer: Error correction and detection, retransmission of packets, sharing of the medium.

20. Wireless & Open System Interconnection Model
Network Layer: Determination of the routing of the information, determination of the QoS and flow control.
Wireless Systems with mobile nodes place greater demands on the network layer.

21. The Decibel
In telecommunications, we are often concerned with the comparison of one power level to another.
The unit of measurement used to compare two power levels is the decibel (dB).
A decibel is not an absolute measurement. It is a relative measurement that indicates the relationship of one power level to another.

22. The Decibel
It is usual in telecommunications to express absolute dB quantities:
i.e. An antenna gain, the free space loss, etc.
All those quantities are being compared with the basic power unit:

23. Exercise 1
An antenna is said to have an output of 25 dB, calculate the actual power of the antenna in Watts.

24. The dBm Another important quantity used in communications is the dBm.
It is, like the dB, a measure of power comparison but with respect to 1mW

25. Exercise 2 & 3
An antenna is said to have an output of 25 dBm, calculate the actual power of the antenna in Watts.
Calculate the Output of the Antenna in dB

26. Usefulness of dB and dBm
It is useful to know that using decibels and logarithms, most of the problems in communications can be simplified.
Example – Formula Simplification:

27. Signals
A signal is an electromagnetic wave that is used to represent and/or transmit information.
An electromagnetic signal is a function that varies with time, but also can be represented as a function of frequency.

28. Time Domain Properties
As a function of time, a signal can be:
Analogue: Intensity varies smoothly over time.
Digital: Maintains a constant intensity over a period of time and then changes to another intensities.

29. Analogue Signal
Intensity

30. Digital Signal
Discrete Levels

31. Periodic & Aperiodic Signals
Signals can be further classified in:
Periodic Signals
Aperiodic Signals
Periodic signals are those that repeat themselves over time:

32. Periodic and Aperiodic Signals
T is called the PERIOD of the signal and is the smallest value that satisfies the equation.
Aperiodic Signals do not comply with the periodicity condition

33. The Sine Wave It is the fundamental analogue signal
It is represented by 3 parameters:
Amplitude,
Frequency - Period
Phase

34. Parameter Definitions
Amplitude: Is the peak value of the intensity (A).
Period: Is the duration in time of 1 cycle (T)
Frequency: Is the rate in cycles/sec [Hz] at which the signal repeats
Phase: Is the measure of the relative position in time with respect of a single period of the signal.

35. Frequency Domain Concepts
In practice an EM signal will be made of many frequency components.
A frequency representation of a signal can also be obtained.
The characterization of the signal if made from another point of view: frequency

36. Frequency Domain

37. THIS IS THE PRINCIPLE OF THE FOURIER ANALYSIS
Frequency Domain
The signal is composed of sinusoidal signals at frequencies f and 3f
If enough sinusoidal signals are added and weighed together, any signal can be represented.
THIS IS THE PRINCIPLE OF THE FOURIER ANALYSIS

38. Frequency Domain
The second frequency of the signal is an integer multiple of the first frequency ( f ).
When all frequency components are integer multiple of one frequency, the latter is referred to as the FUNDAMENTAL FREQUENCY (fo)

39. Frequency Domain
All the other frequency components, are known as the HARMONICS of the signal.
The fundamental frequency is represented by:
The period of the signal is equal to the corresponding period of the fundamental frequency.

40. Summary
Any electromagnetic signal can be shown to consist of a collection of periodic analogue signals (sine waves) at different amplitudes, frequencies and phases.

41. Bandwidth of the Signal
The Spectrum of the signal is the range of frequencies that it contains.
The width of the spectrum is known as the ABSOLUTE BANDWIDTH.

42. Bandwidth of the Signal
Many signals have infinite absolute bandwidth, but with most of the energy contained in a relatively narrow band of frequencies.
This band of frequencies is referred to as the EFFECTIVE BANDWIDTH or simply: “BANDWIDTH”

43. Bandwidth Calculation
For a signal made of the fundamental and two harmonics (odd multiples only), the frequency graph will be the spectrum.
The bandwidth will be the highest frequency minus the fundamental:
BW=5. fo – fo = 4. fo Hz
The bandwidth of a signal is expressed in Hertz.

44. The Wavelength
Another important quantity that goes hand in hand with the frequency is the WAVELENGTH.
It is a measure of the distance (in length units) of the period of the signal. i.e. it is the period of the signal expressed in length units.

45. The Wavelength
The wavelength together with the frequency define the speed at which an electromagnetic signal is travelling through the medium

46. Frequency Domain Visualization
Fourier Transform Principle of Operation

47. The Fourier Transform Theorem
Conditions: Dirichlet Conditions:
x(t) is integrable on the real line (time line)
The number of maxima and minima of x(t) in any finite interval on the real line is finite.
The number of discontinuities of x(t) in any finite interval on the real line is finite.

48. The Fourier Transform Theorem
The Fourier Transform X(f) of x(t) is given by:
The original signal can be obtained back from the Fourier Transform using:

49. The Fourier Transform X(f) is in general a complex function.
Its magnitude and phase, represent the amplitude and phase of various frequency components in x(t).
The function X(f) is sometimes referred to as the SPECTRUM of the signal x(t). (Voltage Spectrum).

50. Fourier Transform Notation

51. Fourier Transform Properties
a) Linearity: The Fourier Transform operation is linear.
b) Duality:

52. Fourier Transform Properties
c) Shift Property: A shift of to in the time domain, causes a phase shift of -2p.f.t0 in the frequency domain:

53. FT: Example 1
The Unit Impulse or delta function is a special function that is defined as:

54. FT: Example 1
The unit impulse is the base for the shifting of functions in time:
The Fourier Transform of the unit impulse yields (using the shift property):

55. FT: Example 2 The unit impulse spectrum is:
Using the Duality Property of the Fourier Transform:

56. Example 3: The Square Pulse
Notation:

57. The Square Pulse

58. The sinc function
If the previous result is plotted with a value of t=1 we obtain the following.

59. Periodic Signals: Fourier Series Representation
The Fourier series is based in the fact that any function can be represented as a sum of sinusoids, this is known as the Fourier Series
A periodic signal x(t) with a fundamental period T0, that meets the dirichlet conditions, can be represented in terms of its Fourier Series as Follows

60. Fourier Series – Sine-Cosine Representation
Fourier Series Expansion of x(t)
where

61. Fourier Series – Amplitude-Phase Representation
This Relates to the sine-cosine as follows

62. Examples Triangular Wave (Period T, Amplitude A)
Sawtooth Wave (Period T, Amplitude A)

63. Fourier Series: Exponential Representation
Where, for some arbitrary a:
and

64. Observations
The coefficients, xn, are called the Fourier series coefficients of x(t).
These coefficients are complex numbers.
The parameter a is arbitrary, It is chosen to simplify the calculation.

65. Useful Parameters Calculated from the Fourier Series Expansion
Given the following Fourier expansion (Amplitude = 2, T=10ms), Calculate:
Amplitude of the Fundamental Component
Amplitude of the 3rd Harmonic
Bandwidth of the Signal for if 5 harmonics are used

66. Solution:

67. Next Week
Solve Tutorial 1
Transmission Fundamentals and Principles