Representation of Band-pass Signal

Similar documents
Digital Band-pass Modulation PROF. MICHAEL TSAI 2011/11/10

Consider a 2-D constellation, suppose that basis signals =cosine and sine. Each constellation symbol corresponds to a vector with two real components

Chapter 10 ACSS Power

Convolutional Codes. Lecture Notes 8: Trellis Codes. Example: K=3,M=2, rate 1/2 code. Figure 95: Convolutional Encoder

I-Hsiang Wang Principles of Communications Lecture 02

PERIODIC STEADY STATE ANALYSIS, EFFECTIVE VALUE,

I-Hsiang Wang Principle of Communications Lecture 02

A First Course in Digital Communications

Outline. Digital Communications. Lecture 12 Performance over Fading Channels and Diversity Techniques. Flat-Flat Fading. Intuition

Communication Systems Lecture 21, 22. Dong In Kim School of Information & Comm. Eng. Sungkyunkwan University

Fourier Series Summary (From Salivahanan et al, 2002)

A MAXIMUM-LIKELIHOOD DECODER FOR JOINT PULSE POSITION AND AMPLITUDE MODULATIONS

Weighted OFDMA Time-Frequency Synchronization for Space Solar Power LEO Satellites Networks: Performance and Cost Analysis

Square Root Raised Cosine Filter

8 PAM BER/SER Monte Carlo Simulation

PH 221-2A Fall Waves - I. Lectures Chapter 16 (Halliday/Resnick/Walker, Fundamentals of Physics 9 th edition)

The Transactional Nature of Quantum Information

Determination of Active and Reactive Power in Multi-Phase Systems through Analytical Signals Associated Current and Voltage Signals

Principles of Communications Lecture 8: Baseband Communication Systems. Chih-Wei Liu 劉志尉 National Chiao Tung University

a) Find the compact (i.e. smallest) basis set required to ensure sufficient statistics.

On Constant Power Water-filling

Impact of Imperfect Channel State Information on ARQ Schemes over Rayleigh Fading Channels

CHAPTER 1: INTRODUCTION

Chapter 10 Objectives

Mobile Communications TCS 455

Signal Design for Band-Limited Channels

Chapter 10: Sinusoidal Steady-State Analysis

Finite-State Markov Modeling of Flat Fading Channels

Periodic Motion is everywhere

Digital Communications: A Discrete-Time Approach M. Rice. Errata. Page xiii, first paragraph, bare witness should be bear witness

Chapter 1: Basics of Vibrations for Simple Mechanical Systems

PH 222-2C Fall Electromagnetic Oscillations and Alternating Current. Lectures 18-19

Force and dynamics with a spring, analytic approach

A New Algorithm for Reactive Electric Power Measurement

IDAN Shock Mount Isolation Vibration Study November 1, The operation of shock and vibration isolation base plate

Analysis of Bit Error Rates for Multiple Access CSK and DCSK Communication Systems

Chapter 2 Random Processes

Page 1. Physics 131: Lecture 22. SHM and Circles. Today s Agenda. Position. Velocity. Position and Velocity. Acceleration. v Asin.

N-Point. DFTs of Two Length-N Real Sequences

BEF BEF Chapter 2. Outline BASIC PRINCIPLES 09/10/2013. Introduction. Phasor Representation. Complex Power Triangle.

Improved digital backward propagation for the compensation of inter-channel nonlinear effects in polarization-multiplexed WDM systems

This model assumes that the probability of a gap has size i is proportional to 1/i. i.e., i log m e. j=1. E[gap size] = i P r(i) = N f t.

Transverse waves. Waves. Wave motion. Electromagnetic Spectrum EM waves are transverse.

Detection and Estimation Theory

Pattern Recognition and Machine Learning. Artificial Neural networks

Actuators & Mechanisms Actuator sizing

Multi-Scale/Multi-Resolution: Wavelet Transform

Upper and Lower Bounds on the Capacity of Wireless Optical Intensity Channels

OSCILLATIONS AND WAVES

Design of Spatially Coupled LDPC Codes over GF(q) for Windowed Decoding

Partition-Based Distribution Matching

PHYS 102 Previous Exam Problems

Supervised assessment: Modelling and problem-solving task

Analog Electronics 2 ICS905

DISSIMILARITY MEASURES FOR ICA-BASED SOURCE NUMBER ESTIMATION. Seungchul Lee 2 2. University of Michigan. Ann Arbor, MI, USA.

Power Spectral Density of Digital Modulation Schemes

The Chebyshev Matching Transformer

Lecture 8 Symmetries, conserved quantities, and the labeling of states Angular Momentum

Chapter 10: Sinusoidal Steady-State Analysis

ENSC327 Communications Systems 2: Fourier Representations. Jie Liang School of Engineering Science Simon Fraser University

that efficiently utilizes the total available channel bandwidth W.

Physics Dynamics: Forces. Science and Mathematics Education Research Group

1. Band-pass modulations. 2. 2D signal set. 3. Basis signals p(t)cos(2πf 0 t) e p(t)sin(2πf 0 t) 4. Costellation = m signals, equidistant on a circle

BEE604 Digital Signal Processing

PARAMETER IDENTIFICATION OF A FEED DRIVE FOR HIGH SPEED MACHINE TOOLS

CHANNEL CAPACITY CALCULATIONS FOR M ARY N DIMENSIONAL SIGNAL SETS

Characterization of the Line Complexity of Cellular Automata Generated by Polynomial Transition Rules. Bertrand Stone

Modulation & Coding for the Gaussian Channel

Rateless Codes for MIMO Channels

4196 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 64, NO. 10, OCTOBER 2016

Chapter 16 Solutions

Adaptive Congestion Control in ATM Networks

Chapter 2 General Properties of Radiation Detectors

A remark on a success rate model for DPA and CPA

Physics 207 Lecture 18. Physics 207, Lecture 18, Nov. 3 Goals: Chapter 14

Representation of Signals & Systems

The accelerated expansion of the universe is explained by quantum field theory.

Lecture 4 Normal Modes

Summary II: Modulation and Demodulation

Rotary Inverted Pendulum stabilization with time delays using BAT optimization

PULSE-TRAIN BASED TIME-DELAY ESTIMATION IMPROVES RESILIENCY TO NOISE

Construction of One-Bit Transmit-Signal Vectors for Downlink MU-MISO Systems with PSK Signaling

EE5900 Spring Lecture 4 IC interconnect modeling methods Zhuo Feng

Order Recursion Introduction Order versus Time Updates Matrix Inversion by Partitioning Lemma Levinson Algorithm Interpretations Examples

FUTURE wireless communication systems are expected to

Genetic Quantum Algorithm and its Application to Combinatorial Optimization Problem

Estimation of ADC Nonlinearities from the Measurement in Input Voltage Intervals

Warning System of Dangerous Chemical Gas in Factory Based on Wireless Sensor Network

Summary: SER formulation. Binary antipodal constellation. Generic binary constellation. Constellation gain. 2D constellations

Electromagnetic scattering. Graduate Course Electrical Engineering (Communications) 1 st Semester, Sharif University of Technology

Figure 1: Equivalent electric (RC) circuit of a neurons membrane

Physics 215 Winter The Density Matrix

General Properties of Radiation Detectors Supplements

Achievable Rates for Shaped Bit-Metric Decoding

Oscillations: Review (Chapter 12)

ω 0 = 2π/T 0 is called the fundamental angular frequency and ω 2 = 2ω 0 is called the

Lecture 16: Scattering States and the Step Potential. 1 The Step Potential 1. 4 Wavepackets in the step potential 6

Intelligent Systems: Reasoning and Recognition. Artificial Neural Networks

Frame with 6 DOFs. v m. determining stiffness, k k = F / water tower deflected water tower dynamic response model

Vulnerability of MRD-Code-Based Universal Secure Error-Correcting Network Codes under Time-Varying Jamming Links

Transcription:

EGR 544 Counication heory 5. Representation of Diitally Modulated Sinals Z. Aliyaziciolu Electrical and Coputer Enineerin Departent Cal Poly Poona Suary Representation of Band-pass Sinal Band-pass sinal s(t) S( f ) f -f c f c Pre-envelope Sinal s + (t) S + ( f ) f c f Equivalent low-pass Sinal s l (t)=+j S l ( f ) f c f Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6

Representation of Band-pass Sinal s(t) s () t = x() t + jy() t l Band-pass sinals can be represented in three different standard notations Quadrature Notation s() t = x()cos( t π f t) y()sin( t π f t) c where and are real-valued base-band sinals, they are called the inphase and quadrature coponents of s(t) Coplex Envelope Notation j { π fct jπ fct l } { } st () = Re s() te = Re[ xt () + jyt ()] e where s l (t) is coplex envelope of s(t) c Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 3 Representation Diitally odulated sinal Modulator aps the diital inforation into analo wavefor that atch the characteristic of the channel It takes blocks of k=lo M binary diits at a tie fro the inforation sequence {a n } and represents one of the deterinistic value M= k. he odulated wavefor is {s (t), =1,,,M} for transission over the channel Meoryless Modulation: he appin fro sequence {a n } to the wavefors {s (t)} is perfored without any constraint on previously transitted wavefor. Meory Modulation: he appin fro sequence {a n } to the wavefors {s (t)} is perfored depend on the one or ore previously transitted wavefor. Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 4

Meoryless Modulation Medhods Pulse-Aplitude Modulation (PAM) sinal PAM is also called Aplitude-shift Keyin ASK) PAM sinal wavefor representation jπ fct { } s () t = Re A () t e = A t ( )cos π ft, = 1,,..., M, 0 t c where { A, = 1,,..., M} denotes the set of M possible aplitude and (t) is sinal pulse shape A takes the discrete values A = ( 1 M) d, = 1,,..., M where d is the distance between adjacent sinal aplitudes Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 5 Pulse-Aplitude Modulation(PAM) sinal M= 0 1 M=4 00 01 11 10 his appin is called Gray Codin M=8 000 001 011 010 110 111 101 100 000 Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 6

Pulse-Aplitude Modulation(PAM) sinal If R show the # bit per second {R [bit/s]}. he tie interval will be b 1 = R is called bit interval he sybol rate is R/ k k = = kb R he M PAM sinal eneries ε = sdt 0 1 = A () t dt 0 1 = Aε, then the sybol interval will be Where ε denotes the enery of pulse (t) Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 7 Pulse-Aplitude Modulation(PAM) sinal Let s define s (t) with unit-enery sinal wavefor s() t = s f() t where f() t = ()cos t π fct ε Unit-enery wavefor 1 s = A ε = 1,,..., M Euclidean distance between any pair of sinal points is d = ( s s ) ( e) n n 1 = ε A An = d ε n he iniu distance d d ε ( e) in = Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 8

Pulse-Aplitude Modulation(PAM) sinal For SSB PAM can be represented j f t { ˆ } c s () t = Re A [ () t ± ()] t e π Where ˆ( t) is the Hilbert ransfor of (t) he Bandwidth is half of the DSM sinal he siple representation of s (t) s () t = A (), t = 1,,..., M Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 9 Diital Phase-Modulated sinals Diital PM is also called Phase-shift keyin (PSK) he M sinal wavefors can be represented in PM π ( 1) j jπ fct M s() t = Re () t e e, = 1,,..., M Or π ( 1) s() t = ()cos t π fct+, = 1,,..., M π( 1) π( 1) = ()cos t cos( π fct) ()sin t sin( π fct) Where (t) is the sinal pulse shape and θ =π (-1)/M, =1,,..,M are the M possible phases of the carrier. Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 10

Diital Phase-Modulated sinals Diital PM sinal has sae enery and ε = 0 sdt 1 1 ε = () t dt = 0 s (t) can be expressed as a linear cobination of two orthoonal sinal s() t = s f () t + s f () t 1 1 where t = [ f1 t f t ] f( ) ( ) ( ) f( t) = ( t)cos π fct ( t)sinπ fct ε ε [ s s ] s = 1 ε π( 1) ε π( 1) s = cos sin Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 11 Diital Phase-Modulated sinals Sinal Space Diara of PSK M= M=4 0 1 01 10 00 11 QPSK M=8 011 010 001 110 000 111 100 101 M=4 01 10 00 11 π/qpsk Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 1

Diital Phase-Modulated sinals he Euclidean distance between two sinal points are ( e) dn = s sn 1/ π ( 1) = ε 1 cos he iniu distance ( e) d in = ε 1 cos π M 1/ Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 13 Quadrature Aplitude Modulation he sinal wavefor is Or jπ fct { } s () t = Re[ A + ja ] () t e c s = A t ()cos π ft A t ()sin π ft, = 1,,..., M, 0 t c c s c jθ jπ fct { } s () t = Re[ V e ] () t e = Vt ( )cos( π ft+ θ ), = 1,,..., M, 0 t c where V = A + A c s θ = tan 1 A A s c Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 14

Quadrature Aplitude Modulation s (t) can be expressed as a linear cobination of two orthoonal sinal s() t = s f () t + s f () t 1 1 where t = [ f1 t f t ] f( ) ( ) ( ) f( t) = ( t)cos π fct ( t)sinπ fct ε ε [ s s ] s 1 = s ε ε = A A c s he Euclidean distance between two sinal points are d = s s ( e) n n 1 = ε A + A + A + A [( c nc) ( s ns) ] Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 15 1/ he iniu distance d = d ε ( e) in Quadrature Aplitude Modulation Sinal space diara of QAM Cal Poly Poona Electrical & Coputer Enineerin Dept. EGR 544-6 16