Modulation Principles



Similar documents
Dispersion in Optical Fibres

Probability and Random Variables. Generation of random variables (r.v.)

Intuitive Guide to Principles of Communications By Charan Langton

Convolution, Correlation, & Fourier Transforms. James R. Graham 10/25/2005

Appendix D Digital Modulation and GMSK

Digital Modulation. David Tipper. Department of Information Science and Telecommunications University of Pittsburgh. Typical Communication System

Performance of Quasi-Constant Envelope Phase Modulation through Nonlinear Radio Channels

RAJALAKSHMI ENGINEERING COLLEGE MA 2161 UNIT I - ORDINARY DIFFERENTIAL EQUATIONS PART A

EE2/ISE2 Communications II

Math 241, Exam 1 Information.

5 Signal Design for Bandlimited Channels

EE 179 April 21, 2014 Digital and Analog Communication Systems Handout #16 Homework #2 Solutions

Section 2.7 One-to-One Functions and Their Inverses

A QUICK GUIDE TO THE FORMULAS OF MULTIVARIABLE CALCULUS

Contents. A Error probability for PAM Signals in AWGN 17. B Error probability for PSK Signals in AWGN 18

Methods for Vibration Analysis

Experiment 3: Double Sideband Modulation (DSB)

Math Assignment 6

TRANSFORM AND ITS APPLICATION

The Hilbert Transform and Empirical Mode Decomposition as Tools for Data Analysis

From Fundamentals of Digital Communication Copyright by Upamanyu Madhow,

CITY UNIVERSITY LONDON. BEng Degree in Computer Systems Engineering Part II BSc Degree in Computer Systems Engineering Part III PART 2 EXAMINATION

r (t) = 2r(t) + sin t θ (t) = r(t) θ(t) + 1 = 1 1 θ(t) Write the given system in matrix form x = Ax + f ( ) sin(t) x y z = dy cos(t)

by Anurag Pulincherry A THESIS submitted to Oregon State University in partial fulfillment of the requirements for the degree of Master of Science

Review of Fourier series formulas. Representation of nonperiodic functions. ECE 3640 Lecture 5 Fourier Transforms and their properties

Implementation of Digital Signal Processing: Some Background on GFSK Modulation

Department of Electrical and Computer Engineering Ben-Gurion University of the Negev. LAB 1 - Introduction to USRP

UNIVERSITY OF CALIFORNIA, SAN DIEGO Electrical & Computer Engineering Department ECE Fall 2010 Linear Systems Fundamentals

The continuous and discrete Fourier transforms

Chapter 2. Parameterized Curves in R 3

MODULATION Systems (part 1)

Solutions for Review Problems

NRZ Bandwidth - HF Cutoff vs. SNR

Introduction to Complex Numbers in Physics/Engineering

Software Defined Radio

3. Regression & Exponential Smoothing

MATH 425, PRACTICE FINAL EXAM SOLUTIONS.

2.2 Separable Equations

Part IB Paper 6: Information Engineering LINEAR SYSTEMS AND CONTROL Dr Glenn Vinnicombe HANDOUT 3. Stability and pole locations.

Fundamentals of Satellite Communications Part 3

T = 10-' s. p(t)= ( (t-nt), T= 3. n=-oo. Figure P16.2

Solutions to Practice Problems for Test 4

Synthetic Aperture Radar (SAR)

CHAPTER 6 Frequency Response, Bode Plots, and Resonance

Bandpass communication and the Complex Envelope

COMPLEX NUMBERS AND PHASORS

Solution: F = kx is Hooke s law for a mass and spring system. Angular frequency of this system is: k m therefore, k

LINEAR MAPS, THE TOTAL DERIVATIVE AND THE CHAIN RULE. Contents


Differentiation of vectors

CURVATURE. 1. Problems (1) Let S be a surface with a chart (φ, U) so that. + g11 g 22 x 1 and g 22 = φ

Trigonometry Hard Problems

Using the Impedance Method

Chapter 8 - Power Density Spectrum

MATH 381 HOMEWORK 2 SOLUTIONS

Review Solutions MAT V (a) If u = 4 x, then du = dx. Hence, substitution implies 1. dx = du = 2 u + C = 2 4 x + C.

Lecture 8 ELE 301: Signals and Systems

SIGNAL PROCESSING & SIMULATION NEWSLETTER

Communication Systems

Student name: Earlham College. Fall 2011 December 15, 2011

Ralph L. Brooker, Member, IEEE. Andrew Corporation, Alexandria, VA 22314, USA

LABORATORY 10 TIME AVERAGES, RMS VALUES AND THE BRIDGE RECTIFIER. Bridge Rectifier

Algebra 2: Themes for the Big Final Exam

CIRCUITS LABORATORY EXPERIMENT 3. AC Circuit Analysis

Power Spectral Density

Frequency Domain and Fourier Transforms

Introduction to Frequency Domain Processing 1

Solutions to Homework 5

College of the Holy Cross, Spring 2009 Math 373, Partial Differential Equations Midterm 1 Practice Questions

PHASE ESTIMATION ALGORITHM FOR FREQUENCY HOPPED BINARY PSK AND DPSK WAVEFORMS WITH SMALL NUMBER OF REFERENCE SYMBOLS

Homework #1 Solutions

1995 Mixed-Signal Products SLAA013

All About Pulse Modulation How Ultra Narrow Band Modulation works Updated 12/15//10

Second Order Systems

Section 14.4 Chain Rules with two variables

Spike-Based Sensing and Processing: What are spikes good for? John G. Harris Electrical and Computer Engineering Dept

SAT Math Facts & Formulas

16.2 Periodic Waves Example:

Vector surface area Differentials in an OCS

Mechanical Vibrations Overview of Experimental Modal Analysis Peter Avitabile Mechanical Engineering Department University of Massachusetts Lowell

Mechanical Properties - Stresses & Strains

Analog Filters. A common instrumentation filter application is the attenuation of high frequencies to avoid frequency aliasing in the sampled data.

Analog and Digital Signals, Time and Frequency Representation of Signals

TCOM 370 NOTES 99-4 BANDWIDTH, FREQUENCY RESPONSE, AND CAPACITY OF COMMUNICATION LINKS

Spin Hall Magnetoresistive Noise

Scalar Valued Functions of Several Variables; the Gradient Vector

ANALYTICAL METHODS FOR ENGINEERS

The two dimensional heat equation

Vector Spaces; the Space R n

Optical Fibres. Introduction. Safety precautions. For your safety. For the safety of the apparatus

( 1 ) Obtain the equation of the circle passing through the points ( 5, - 8 ), ( - 2, 9 ) and ( 2, 1 ).

An exact formula for default swaptions pricing in the SSRJD stochastic intensity model

Higher Order Equations

Digital Baseband Modulation

The Vector or Cross Product

Transcription:

EGR 544 Communiation Theory 5. Charaterization of Communiation Signas and Systems Z. Aiyaziiogu Eetria and Computer Engineering Department Ca Poy Pomona Moduation Prinipes Amost a ommuniation systems transmit digita data using s sinusoida arrier waveform The transmitted hanne has imited band-width and is entered about the arrier for doube side moduation is next to arrier signa for singe side. Physia moduation system impementation Proess digita information at baseband Puse shaping and fitering of digita waveform Mixing with arrier signa Fitering RF signa and ampifying to transmission Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5

Moduation Signas representation We an modify ampitude, phase, or frequeny of baseband signa Ampitude Shift Keying (ASK) or On/Off Keying (OOK) Aos( π ft) 0 0 Frequeny Shift Keying (FSK) Phase Shift Keying (PSK) Aos( π ft) 0 Aos( π ft) Aos( π f t) 0 Aos( π f t+ π) = Aos( π f t+ π) Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 3 Representation of Band-Pass Signa The transmitted signa is usuay a rea vaued band-pass signa and et s a s(t) Mathematia mode of a rea-vaued narrowband band-pass signa is S( f) 0 for f f f f + f and f f B B B ½ S - (f)=u(-f)s(f) S( f ) ½ S + (f)=u(f)s(f) f -f f S(f) is Fourier transform of s(t). u(f) is the unit step funtion in frequeny domain Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 4

Representation of Band-Pass Signa Goa is to deveop a mathematia representation in time domain of S + (f ) and S - (f ) The time domain representation of S + (f ) is s + (t), whih is aed pre-enveope of s(t) ft s+ () t = S+ ( f) e df = [ ( ) ( )] ft u f S f e df [ ( )] [ ( )] F u f F S f = j = δ () t + s() t πt j = st () + st () πt = st () + jst ˆ() where st ˆ( ) = st () πt s( τ ) = dτ π t τ Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 5 Representation of Band-Pass Signa sˆ( t) may be onsidered the output of the fiter suh as s() t πt Hibert Transform sˆ( t) The frequeny response of the fiter is π t j f > 0 H( f) = jsgn( f) = 0 f = 0 j f < 0 ft ft H ( f) = h( t) e dt = e dt H( f) = for f 0 π for f > 0 Θ ( f ) = π for f 0 < Fourier Transform of Hibert Transform j F = sgn( f) πt F = jsgn( f) πt Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 6

Representation of Band-Pass Signa s() t sˆ( t) s X + + () t πt Hibert Transform j S( f ) S + (f)=u(f)s(f) f -f f S ( f) = S ( f + f ) f The ow-pass representation of S + (f ) is S( f) = S+ ( f + f) in time domain s () () [ () ˆ t = s+ t e = s t + js() t ] e In ompex form s() t = x()os( t π ) y()sin( t π ) s () t = x() t + jy() t sˆ( t) = x()sin( t π ) + y()os( t π ) x(t) and y(t):quadrature omponents of s (t) Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 7 + Representation of Band-Pass Signa Another representation of the signa Or we an represent {[ ] } st () = Re xt () + jyt () e = Re s ( t) e s () t () j t () = a t e θ st () = Re s () te at () = x() t + y() t jθ () t = Re ate ( ) e = at ()os ft+ () t [ π θ ] yt () θ () t = tan x() t a(t) is aed enveope of s(t) and θ(t) is aed the phase of s(t) Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 8

Representation of Band-Pass Signa The energy in the signa s(t) is defined as f t { } ε = s () t dt = Re s () t e dt Using representation of s(t) in osine form Then { [ ]} ε = s () t dt = a ()os t π f t+ θ () t dt ε = π θ + + { [ ]} a () t dt a ()os4 t f t () t dt a(t) is the enveope and varies sowy reative to osine funtion ε = a () t dt s () t dt = Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 9 Representation of Linear Band-Pass signa A inear fiter or system an be represented either h(t) or of H(f). Sine h(t) is rea H( f) = H ( f) Let s define H ( f f ) H( f) f > 0 H( f f) = 0 f < 0 Then, we have And H ( - f f ) H ( f f) = H f H f f H f f ( ) = ( ) + ( ) 0 f > 0 H f f ( ) < 0 The Inverse transform of H(f) π ht () = h() te + h () te = Re h ( t) e j f t h (t), inverse transform of H (f), is impuse response of ow-pass system and is omex Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 0

Response of Band-pass System to a Band-pass signa s(t) h(t) r(t) Let s have s(t) narrowband band-pass signa and is the equivaent ow-pass signa s (t). Band-pass fiter (system) the impuse response h(t) and its equivaent ow-pass impuse response h (t) The output of the band-pass fiter is r(t) aso band-pass signa rt = j () Re r () te π Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 Response of Band-pass System to a Band-pass signa r(t) an be given as rt () = s( τ ) ht ( dτ In frequeny domain R( f) = S( f) H( f) R( f) = S( f f) + S ( f f) H( f f) + H( f f) For narrow band signa s(t) and narrow band system h(t) S f f H f f ( ) ( ) = 0 R f S f f H f f S f f H f f ( ) = ( ) ( ) + ( ) ( ) R f R f f R f f ( ) = ( ) + ( ) S ( f f ) H ( f f ) = 0 R( f) = S ( f) H ( f) Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 r() t = s ( τ ) h( t dτ

Bandpass Stationary Stohasti Proess Let s have n(t) as narrowband band-pass proess with spetra density is muh smaer than f, zero mean and power spetra density Φ nn (f). And we an represent it as nt () = at ()os [ π ft + θ() t] = x()os( t π ) y()sin( t π ) j = Re zte ( ) π a(t) is the enveope and θ(t) is the phase of the rea vaued signa. x(t) and y(t) are the quadrature omponent of n(t). z(t) is the ompex enveope of n(t) n(t) is zero mean, therefore x(t) and y(t) wi be zero mean, The autoorreation and ross-orreation funtion satisfy φxx( τ ) = φyy( τ ) φ ( τ ) = φ ( τ ) xy yx Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 3 Bandpass Stationary Stohasti Proess The autoorreation funtion φ nn ( of n(t) {[ ] [ x( t+ os π f ( t+ y( t+ sin π f ( t+ ] } φ ( = Entnt [ ( ) ( + ] = E xt ( )os π ft yt ( )sinπ ft nn φ ( τ ) = φ ( osπ f tos π f ( t+ + φ ( sinπ f tsin π f ( t+ nn xx yy φ ( ]sin π f tos π f ( t+ φ osπ f tsin π f ( t+ xy yx Using trigonometri identities φnn( τ ) = [ φxx( τ ) + φyy( ]os π fτ + [ φxx( τ ) φyy( ]os π f( t+ [ φyx( τ ) φxy( ]sin π fτ [ φ yx( τ ) + φxy( ]sin π f( t+ Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 4

Bandpass Stationary Stohasti Proess Using zero mean properties φ ( τ ) = φ ( os π fτ + φ ( sinπ fτ nn xx yx z(t) an be given ompex-vaued as z(t)=x(t)+jy(t) The autoorreation funtion of z(t) is given as φzz( = Ez [ ( tzt ) ( + ] = [ φxx ( τ ) + φyy ( τ ) jφ xy ( τ ) + jφ yx ( τ )] = φ ( + φ ( xx The autoorreation funtion φ nn ( of n(t) an be obtained by φ zz ( and the arrier frequeny f yy φ τ φ τ j nn( ) = Re zz( ) e π Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 5 Bandpass Stationary Stohasti Proess The Fourier transform of the autoorreation funtion φ nn ( gives The power spetra density Φ nn (f) j π f t j π f τ f zz e e d Φ ( ) = Re φ ( τ nn = Φ +Φ [ ( f f ) ( f f )] zz zz Where Φ zz (f) is the power density spetrum of equivaent owpass proess z(t). Φ zz (f) is rea-vaued funtion and the autoorreation funtion of z(t) satisfy that φ τ φ τ zz( ) = zz( ) Ca Poy Pomona Eetria & Computer Engineering Dept. EGR 544-5 6