Wireless Communications Systems

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Wireless Communications Systems

• Dr. Jose A. Santos

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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.

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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.

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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.

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Learning Outcomes

1. Understand different Wireless LANs technologies
   and Identify key elements that characterize the
   protocol architecture of such technologies.
2. 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

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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)

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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)

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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)

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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)

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Course Content
Subject Area 4 Wireless LANs

• Wireless LAN Technologies (Week 12)
• IEEE 802.11 Wireless LAN Standards (Mandatory
  Reading)
• Bluetooth (Mandatory Reading)

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Course Content
Subject Area 5 MATLAB Practicals

• Introduction to MATLAB, Fourier Analysis Power
  Spectrum Generation (Week 2-3)
• Functions in MATLAB, Modulation Techniques (AM,
  FM, ASK, FSK) (Week 5-6)
• Introduction to Simulink, Basic Communications
  Models, Error Control, Modulation Systems. (Week
  7-8)
• Laboratory Exam (Week 12)

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Teaching Schedule Evaluation

• End of year Examination (75)
• Covers Learning Outcomes 1,3 and 4
• 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 Module
  Handout Document (Module Website).

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Course Reading List

• Essential
• Stallings, W. Wireless Communications and
  Networks, Prentice Hall. 2002 and 2nd Ed. 2005.
• 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. 2002.
• Proakis, J. Communication Systems Engineering
  2nd Ed. Prentice Hall, 2002.
• Haykin, S. and Moher, M. Modern Wireless
  Communications, International Ed. Prentice Hall,
  2005.

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Module Delivery

• Class Structures
• Theory Class 2 Hours every week
• Tutorials 1 Hours (Every week)
• Labs (3 Hour Labs)
• Availability and Contact
• Dr. Jose A. Santos
• Room MG121E
• ja.santos_at_ulster.ac.uk
• http//www.scis.ulster.ac.uk/jose

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Introduction to Wireless Systems
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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

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Class Contents

• Introduction to Fourier Analysis of Signals
• The Fourier Transform Theorem
• The Fourier Series Representation

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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

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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.

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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.

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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.

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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
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Exercise 1

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

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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

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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

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Output on dB
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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

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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.

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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.

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Analogue Signal
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Digital Signal
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Periodic Aperiodic Signals

• Signals can be further classified in
• Periodic Signals
• Aperiodic Signals
• Periodic signals are those that repeat themselves
  over time

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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

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The Sine Wave

• It is the fundamental analogue signal
• It is represented by 3 parameters
• Amplitude,
• Frequency - Period
• Phase

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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.

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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

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Frequency Domain
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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

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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)

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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.

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Summary

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

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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.

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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

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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
• BW5. fo fo 4. fo Hz
• The bandwidth of a signal is expressed in Hertz.

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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.

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The Wavelength

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

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Frequency Domain Visualization

• Fourier Transform Principle of Operation

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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.

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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

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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).

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Fourier Transform Notation
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Fourier Transform Properties

• a) Linearity The Fourier Transform operation is
  linear.
• b) Duality

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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

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FT Example 1

• The Unit Impulse or delta function is a special
  function that is defined as

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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)

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FT Example 2

• The unit impulse spectrum is
• Using the Duality Property of the Fourier
  Transform

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Example 3 The Square Pulse
Notation
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The Square Pulse
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The sinc function

• If the previous result is plotted with a value of
  t1 we obtain the following.

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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

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Fourier Series Sine-Cosine Representation

• Fourier Series Expansion of x(t)
• where

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Fourier Series Amplitude-Phase Representation

• Representation
• This Relates to the sine-cosine as follows

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Examples

• Triangular Wave (Period T, Amplitude A)
• Sawtooth Wave (Period T, Amplitude A)

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

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Useful Parameters Calculated from the Fourier
Series Expansion

• Given the following Fourier expansion (Amplitude
  2, T10ms), Calculate
• Amplitude of the Fundamental Component
• Amplitude of the 3rd Harmonic
• Bandwidth of the Signal for if 5 harmonics are
  used

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Solution
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Next Week

• Solve Tutorial 1
• Transmission Fundamentals and Principles