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ECNG 6706 - Antennas and RadiationIntroduction
Sean Rocke
September 8
th
, 2014
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Outline
1 Course Introduction
2
Dig Comms Overview
3 Course Tools
4 Conclusion
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Course Introduction
Course Administration
Lets take a look at the CourseOutline...
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Dig Comms Overview
Elements of a Digital Communications System
Lets take a look at the CommsProgramme Overview...
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Dig Comms Overview
Communications Channels
Wireline Channels
Wireless Channels
Fiber-Optic Channels
Underwater Acoustic Channels
Storage Channels
THE BODY!!!!
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Dig Comms Overview
Mathematical Models for Communications Channels
1 Additive Noise Channelr(t) = s(t) +n(t)
2 Linear Time Invariant (LTI) Filter Channel
r(t) =s(t) c(t) +n(t) =
c()s(t )d+n(t)
3 Linear Time-Variant (LTV) Fiter Channelr(t) =s(t) c(; t) +n(t) =
c(; t)s(t )d+n(t)Mobile
cellular channel example
LTV filter -c(; t) =L
k=1 k(t)( k)
Received signal -r(t) =L
k=1 k(t)s(t k) +n(t)
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Course Tools
ECNG 6706 Tools
ECNG 6706 will leverage both analytical and computeraided tools foranalysis of digital communications systems:
Analytical Tools:
Mostly B.O.M.D.A.S.+ Trigonometry . . .Circuit Theory
Electromagnetic Field TheoryProbability & Random Process TheoryLinear Algebra (i.e., Vector & Matrix Algebra)Signals and Systems Analysis (e.g., Fourier, Laplace)
Computeraided Tools:
MATLAB & Simulink (Simscape, SimRF, RF Toolbox, CommsToolbox,. . . )COMSOLSpreadsheets (seriously!) . . . :-)
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C T l
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Course Tools
Module 1 - Math Primer
Polynomial approximations - Taylor & Maclaurins Series
Sum/product of sines/cosines
Complex envelope signal representation
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Course Tools
Polynomial Approximations
Many exist (e.g., Taylor, Maclaurin,. . . )
Taylor Series:
Function representation as aninfinite seriesbased on value of
functions derivativesat a single point
f(x) =
n=0f(n)(a)
n! (x a)n =f(a) + f
(a)1! (x a) +
f(a)2! (x a)
2 +
Only works under certain conditions!!!
Ifa= 0, Taylor series= Maclaurin series
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Course Tools
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Course Tools
Polynomial Approximations
Example 1:
Using the Taylor series expansions ata=0, prove the following:
1 ex =1 +x+ x2
2! + x3
3! + x4
4! + x5
5! +
2 cos(x) =1 x2
2! + x4
4! x6
6! + x8
8!
3 sin(x) =x x3
3! + x5
5! x7
7! + x9
9!
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Course Tools
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Course Tools
Polynomial Approximations
Figure:sin(x) and its Taylor series approximations, up to order 13. Source:Wikipedia.
Question:
So whats the point of the Taylor series for thiscourse?!?!
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Course Tools
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Course Tools
Sum/product of sines/cosines
Product Sum:cos(A)cos(B) = cos(AB)+cos(A+B)
2
sin(A)sin(B) = cos(AB)cos(A+B)2
sin(A)cos(B) = sin(A+B)+sin(AB)2
cos(A)sin(B) =
sin(A+B)sin(AB)
2Sum Product:
sin(A) sin(B) =2sinAB
2
cos
AB
2
cos(A) +cos(B) =2cosA+B
2
cos
AB
2
cos(A) cos(B) = 2sinA+B
2
sin
AB
2
Shifts:sin(A+
2) =cos(A)
cos(A+ 2) = sin(A)
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Course Tools
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Course Tools
Complex Envelope
Baseband SignalSignal with frequency content only in the vicinity of DC (i.e., 0Hz)Complex envelope: x(t) =xI(t) +jxQ(t)xI(t)- In-phase component, xQ(t)- Quadrature component
Bandpass SignalSignal with frequency content not in the vicinity of DCx(t) = R[x(t)ejct]
c=2fc- Carrier frequency
Figure:Baseband vs Bandpass Spectrum. Based upon: Kolumban et al
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Course Tools
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Course Tools
Complex Envelope
Figure:Baseband Bandpass Conversion. Based upon: Kolumban et al(2012).
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Course Tools
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Receiver Architecture Examples
Figure:Receiver Architecture Examples. Basedupon:Cruzetal(2010).
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Course Tools
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Transmitter Architecture Examples
Figure:Receiver Architecture Examples. Based upon: Cruz et al (2010).
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Course Tools
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Transceiver IC Examples
Figure:Analog Devices FMCOMMS 4 1x1 Agile RF Transceiver. Source:Analog.com.
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Course Tools
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KEy Concepts Review
Baseband upconversion to bandpass can be achieved via
modulation, requiring a mixer circuitBandpass downconversion to baseband can be achieved via
demodulation, requiring a mixer circuit
Mixing can be achieved using devices with nonlinear VI
characteristics (e.g., diodes, transistors)Nonlinear characteristics produce mixing effect as seen from
Taylor series expansion of some nonlinear functions
Mixing produces output frequencies that are the sum and
difference of the input frequencies (and possible harmonics)
Filtering removes unwanted frequencies and harmonics
Many transceiver architectures exist with different strengths and
weaknesses, allowing for some choice in transceiver design for
the various communications channel types
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Conclusion
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Conclusion
We covered:
Course Overview
Dig Comms Systems Overview
Course Tools
Your goals for next class:
Install and familiarize yourself with MATLAB
Review readings on Radio Architectures in prep for next class
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Q & A
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Thank You
Questions????
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