PULSE SHAPING AND RECEIVE FILTERING

Similar documents
Digital Communication System

Digital Communication System

1. Clearly circle one answer for each part.

Principles of Baseband Digital Data Transmission

Line Coding for Digital Communication

ANALOG (DE)MODULATION

Chapter-2 SAMPLING PROCESS

Revision of Wireless Channel

CARRIER RECOVERY. Phase Tracking. Frequency Tracking. adaptive components. Squared Difference Phase-locked Loop Costas Loop Decision Directed

Communication Channels

EITG05 Digital Communications

CHANNEL ENCODING & DECODING. Binary Interface

1. Clearly circle one answer for each part.

Objectives. Presentation Outline. Digital Modulation Lecture 03

Exercises for chapter 2

Fund. of Digital Communications Ch. 3: Digital Modulation

STUFF HAPPENS. A Naive/Ideal Communication System Flat Fading What if... idealized system. 9: Stuff Happens

Handout 13: Intersymbol Interference

Lab 3.0. Pulse Shaping and Rayleigh Channel. Faculty of Information Engineering & Technology. The Communications Department

Chpater 8 Digital Transmission through Bandlimited AWGN Channels

Fundamentals of Digital Communication

Text Book: Simon Haykin & Michael Moher,

LOOKING AT DATA SIGNALS

1B Paper 6: Communications Handout 2: Analogue Modulation

Revision of Lecture 3

HW 6 Due: November 3, 10:39 AM (in class)

EE3723 : Digital Communications

DIGITAL FILTERING AND THE DFT

SAMPLING WITH AUTOMATIC GAIN CONTROL

Chapter 7: Pulse Modulation

Refresher on Digital Communications Channel, Modulation, and Demodulation

Theory of Telecommunications Networks

Module 4. Signal Representation and Baseband Processing. Version 2 ECE IIT, Kharagpur

Communications IB Paper 6 Handout 3: Digitisation and Digital Signals

EXAMINATION FOR THE DEGREE OF B.E. Semester 1 June COMMUNICATIONS IV (ELEC ENG 4035)

QUESTION BANK SUBJECT: DIGITAL COMMUNICATION (15EC61)

DT Filters 2/19. Atousa Hajshirmohammadi, SFU

Lab course Analog Part of a State-of-the-Art Mobile Radio Receiver

3.6 Intersymbol interference. 1 Your site here

2.1 BASIC CONCEPTS Basic Operations on Signals Time Shifting. Figure 2.2 Time shifting of a signal. Time Reversal.

Wireless PHY: Modulation and Demodulation

Speech, music, images, and video are examples of analog signals. Each of these signals is characterized by its bandwidth, dynamic range, and the

COURSE OUTLINE. Introduction Signals and Noise Filtering: LPF1 Constant-Parameter Low Pass Filters Sensors and associated electronics

Digital Modulation Schemes

EE6604 Personal & Mobile Communications. Week 10. Modulation Techniques

Computer Networks - Xarxes de Computadors

Sampling and Pulse Trains

Implementation of Digital Signal Processing: Some Background on GFSK Modulation

Handout 11: Digital Baseband Transmission

Exam in 1TT850, 1E275. Modulation, Demodulation and Coding course

Exploring QAM using LabView Simulation *

Outline. Wireless PHY: Modulation and Demodulation. Recap: Modulation. Admin. Recap: Demod of AM. Page 1. Recap: Amplitude Modulation (AM)

ON SYMBOL TIMING RECOVERY IN ALL-DIGITAL RECEIVERS

Communications IB Paper 6 Handout 2: Analogue Modulation

QUESTION BANK EC 1351 DIGITAL COMMUNICATION YEAR / SEM : III / VI UNIT I- PULSE MODULATION PART-A (2 Marks) 1. What is the purpose of sample and hold

Problems from the 3 rd edition

Communications I (ELCN 306)

EE5713 : Advanced Digital Communications

SIGNALS AND SYSTEMS LABORATORY 13: Digital Communication

MSK has three important properties. However, the PSD of the MSK only drops by 10log 10 9 = 9.54 db below its midband value at ft b = 0.

WIRELESS COMMUNICATIONS PRELIMINARIES

Linear Time-Invariant Systems

Chapter 9. Digital Communication Through Band-Limited Channels. Muris Sarajlic

Lecture 2: SIGNALS. 1 st semester By: Elham Sunbu

Lecture 10. Digital Modulation

Downloaded from 1

M(f) = 0. Linear modulation: linear relationship between the modulated signal and the message signal (ex: AM, DSB-SC, SSB, VSB).

Other Modulation Techniques - CAP, QAM, DMT

Digital Communication Lecture-1, Prof. Dr. Habibullah Jamal. Under Graduate, Spring 2008

1.Explain the principle and characteristics of a matched filter. Hence derive the expression for its frequency response function.

What if the bandpass and complex baseband signals are random processes? How are their statistics (autocorrelation, power density) related?

ALi Linear n-stage t ShiftRegister output tsequence

Outline. Discrete time signals. Impulse sampling z-transform Frequency response Stability INF4420. Jørgen Andreas Michaelsen Spring / 37 2 / 37

Multi-carrier Modulation and OFDM

Digital communication

Mobile Communications

+ a(t) exp( 2πif t)dt (1.1) In order to go back to the independent variable t, we define the inverse transform as: + A(f) exp(2πif t)df (1.

Transmission Fundamentals

Department of Electronics and Communication Engineering 1

Digital Communication Systems Third year communications Midterm exam (15 points)

Chapter 2 Direct-Sequence Systems

Lecture 3 Concepts for the Data Communications and Computer Interconnection

Amplitude Modulation, II

Outline. EECS 3213 Fall Sebastian Magierowski York University. Review Passband Modulation. Constellations ASK, FSK, PSK.

Spread spectrum. Outline : 1. Baseband 2. DS/BPSK Modulation 3. CDM(A) system 4. Multi-path 5. Exercices. Exercise session 7 : Spread spectrum 1

Principles of Communications ECS 332

Solution to Chapter 4 Problems

Chapter 7 Multiple Division Techniques for Traffic Channels

Chapter 2: Signal Representation

Digital Processing of Continuous-Time Signals

Matched filter. Contents. Derivation of the matched filter

Chapter 6 Passband Data Transmission

Digital Processing of

Chapter 4. Part 2(a) Digital Modulation Techniques

EE4512 Analog and Digital Communications Chapter 6. Chapter 6 Analog Modulation and Demodulation

Communication Systems Lecture-12: Delta Modulation and PTM

Objectives. Presentation Outline. Digital Modulation Revision

Problem Sheets: Communication Systems

Laboratory Assignment 5 Amplitude Modulation

Coded excitations NINE. 9.1 Temporal coding

Transcription:

PULSE SHAPING AND RECEIVE FILTERING Pulse and Pulse Amplitude Modulated Message Spectrum Eye Diagram Nyquist Pulses Matched Filtering Matched, Nyquist Transmit and Receive Filter Combination adaptive components Software Receiver Design Johnson/Sethares/Klein 1 / 24

Pulse Shaping and Receive Filtering Binary message w { 3, 1, 1, 3} sequence b Coding P(f) Pulse shaping Other FDM Transmitted users Noise signal Analog Channel upconversion Carrier specification Analog received signal Antenna Analog conversion to IF T s Input to the software receiver Digital down- conversion to baseband Downsampling Equalizer Decision Decoding Timing synchronization T m Carrier synchronization Q(m) { 3, 1, 1, 3} Pulse matched filter Source and Reconstructed error coding message frame synchronization b^ We will focus on the situation where up and downconversion have been flawlessly performed and the effect of transmission from baseband PAM message waveform to received signal is presumed described by a linear transfer function and the addition of interferers, in particular spectrally flat broadband noise. Message w(kt) { 3, 1, 1, 3} Pulse shaping x(t) Channel Interferers g(t) Noise n(t) Receive filter y(t) Reconstructed message m(kt ) i { 3, 1, 1, 3} Decision p(t) P(f) h c(t) H c(f) h R(t) H R(f) Software Receiver Design Johnson/Sethares/Klein 2 / 24

Pulse and pulse amplitude modulated (PAM) message spectrum Message w(kt) { 3, 1, 1, 3} x(t) Pulse shaping Noise Reconstructed Interferers n(t) message m(kt ) i { 3, 1, 1, 3} g(t) y(t) Receive Channel Decision filter p(t) P(f) h c(t) H c(f) h R(t) H R(f) The spectral footprint of a baseband PAM signal is no wider than that of the pulse shape. Compose the analog pulse train entering the pulse shaping filter as w a (t) = k w(kt)δ(t kt) which is w(kt) for t = kt and for t kt Pulse shaping filter output x(t) = w a (t) p(t) X(f) = W a (f)p(f) X(f) cannot be nonzero at frequencies where P(f) is zero. Software Receiver Design Johnson/Sethares/Klein 3 / 24

Pulse... message spectrum (cont d) One-symbol wide Hamming blip pulse shape (with 1 samples per symbol) and frequency response (from freqz) 1.8 Pulse shape.6.4.2.1.2.3.4.5.6.7.8.9 Sample periods (a) Spectrum of the pulse shape 1 2 1 1 2 1 4.1.2.3.4.5.6.7.8.9 1 Normalized frequency (b) Software Receiver Design Johnson/Sethares/Klein 4 / 24

Pulse... message spectrum (cont d) Spectrally flat 4-PAM symbol sequence triggering baud-spaced 1-times oversampled Hamming blip pulse shape as (baseband) output of pulse shaping filter 3 Output of pulse shaping filter 2 1 1 2 3 5 1 15 2 25 Symbols Spectrum of the output 1 4 1 2 1 1 2 1 4.1.2.3.4.5.6.7.8.9 1 Normalized frequency Message signal spectrum has scalloped contours of Hamming blip pulse frequency response. Software Receiver Design Johnson/Sethares/Klein 5 / 24

Pulse... message spectrum (cont d) Triple-wide Hamming blip 1 The pulse shape.8.6.4.2.5 1 1.5 2 2.5 3 Sample periods (a) Spectrum of the pulse shape 1 2 1 1 2 1 4.1.2.3.4.5.6.7.8.9 1 Normalized frequency (b) Wider pulse shape narrower passband in magnitude spectrum Software Receiver Design Johnson/Sethares/Klein 6 / 24

Pulse... message spectrum (cont d) Spectrally flat 4-PAM symbol sequence triggering three-baud-wide 1-times oversampled Hamming blip pulse shape as (baseband) output of pulse shaping filter Output of pulse shaping filter 5 5 5 1 15 2 25 Symbols 1 4 Spectrum of the output 1 2 1 1 2.1.2.3.4.5.6.7.8.9 1 Normalized frequency Compare message with single-baud-wide Hamming pulse to observe how intersymbol interference of triple-baud-wide Hamming pulse can cause decision errors. Software Receiver Design Johnson/Sethares/Klein 7 / 24

Eye Diagram 11: Pulse Shaping and Receive Filtering Eye diagram is a popular robustness evaluation tool. For 4-PAM, single-baud-wide Hamming blip with additive broadband channel noise, retriggering oscilloscope after every 2 baud intervals produces Optimum sampling times Sensitivity to timing error 3 2 1 Distortion at zero crossings 1 2 3 Noise margin The "eye" kt (k 1)T Observe illustrative vertical (amplitude) and horizontal (timing) margins for correct decision at sample times. Software Receiver Design Johnson/Sethares/Klein 8 / 24

Eye Diagram (cont d) Reconsider multiple-baud-wide Hamming pulse example. Top: Double open-eye Middle: Triple partial eye closure Bottom: Quintuple fully closed eye Software Receiver Design Johnson/Sethares/Klein 9 / 24

Eye Diagram (cont d) Consider 2-symbol wide, 1 times oversampled, truncated, sinc pulse (sin(πt/t)/(πt/t)) with zero-crossings at kt for k = 1,2,...,1) for 4-PAM symbol sequence.6 Using a sinc pulse shape.4.2.2 1 8 6 4 2 2 4 6 8 1 pulse shaped data sequence 4 2 2 4 5 1 15 2 25 symbol number 4 2 2 4 5 1 15 2 25 3 3 baud (and 3 sample) wide eye diagram (symbol times: indices 1, 2, and 3) A multi-baud-wide pulse shape, but no ISI! Software Receiver Design Johnson/Sethares/Klein 1 / 24

Nyquist Pulses 11: Pulse Shaping and Receive Filtering The impulse response of a Nyquist pulse creating no ISI at other sample times is zero at those instants and nonzero only at the one particular sample time. The impulse response p(t) is a Nyquist pulse for a T-spaced symbol sequence if there exists a τ such that { c, k = p(t) t=kt+τ =, k Rectangular pulse: p R (t) = { 1, t < T, otherwise Rectangular pulse is a Nyquist pulse. Software Receiver Design Johnson/Sethares/Klein 11 / 24

Nyquist Pulses (cont d) Sinc pulse: where f = 1/T. p S (t) = sinπf t πf t Sinc is Nyquist pulse because p S () = 1 and p S (kt) = sin(πk) πk =. Sinc envelope decays as 1/t. Raised-cosine pulse: p RC (t) = 2f ( sin(2πf t) 2πf t )[ ] cos(2πf t) 1 (4f t) 2 with roll-off factor β = f /f. Raised-cosine is Nyquist pulse for T = 1/2f because p RC has a sinc factor sin(πk)/πk which is zero for all nonzero integers k. Raised-cosine envelope decays at 1/ t 3. As β, raised-cosine sinc. Software Receiver Design Johnson/Sethares/Klein 12 / 24

Nyquist Pulses (cont d) Raised-cosine pulse (cont d): Fourier transform 1, f < f 1 1+cos(α) P RC (f) = 2, f 1 < f < B, f > B where B is the absolute bandwidth, f is the 6db bandwidth, f = B f, f 1 = f f, and α = π( f f 1) 2f Software Receiver Design Johnson/Sethares/Klein 13 / 24

Nyquist Pulses (cont d) Raised-cosine pulse (cont d): Time and Frequency Plots: 1.5 1.5 3T.5 2T T T 2T 3T 1.5 1 f /2 f 3f /2 2f Software Receiver Design Johnson/Sethares/Klein 14 / 24

Nyquist pulses (cont d) The sum of the frequency responses of a Nyquist pulse shape and its replicas shifted by an integer multiple of the symbol frequency (i.e. the inverse of the symbol period) is a real constant. Consider a candidate Nyquist pulse v(t) that is nonzero at time zero and zero for all other times that are integer multiples of the symbol period T. Using the sifting property of (A.56) rewritten with frequency as the independent variable and utilizing the fact that δ is an even function as V(f) δ(f f ) = V(f f ) yields V(f nf ) = V(f) [ δ(f nf )] n= n= Software Receiver Design Johnson/Sethares/Klein 15 / 24

Nyquist pulses (cont d) From (A.28) with w(t) = 1 and f = 1/T F{T δ(t nt)} = n= Given (A.15) and (A.39) V(f) [ n= δ(f nf )] n= δ(f nf ) = t= [v(t)(t k= δ(t kt))]e j2πft dt = k= Tv(kT)e j2πfkt Because v(kt) is nonzero only for v(), V(f nf ) = Tv() n= Thus, sum of V(f nf ) is a real constant if v(t) is a Nyquist pulse. Converse is also true. Software Receiver Design Johnson/Sethares/Klein 16 / 24

Matched Filter 11: Pulse Shaping and Receive Filtering Suppose the channel simply adds broadband noise n(t). The symbol to reconstructed downsample system is described by n(t) m(kt ) P(f ) g(t) H R (f ) y(t) y(kt ) Pulse shaping Receive filter Downsample n(t) H R (f ) Receive filter w(t) w(kt ) Downsample m(kt ) g(t) v(t) P(f ) H R (f ) v(kt ) y(kt ) Pulse shaping Receive filter Downsample so y(t) = v(t)+w(t) = h R (t) g(t)+h R (t) n(t). Our objective is to choose h R (t) to maximize the power of the signal v(t) at a specific time t = τ, i.e. v 2 (τ), relative to the total power of w(t) where the power spectral density of n(t) is a constant η over all frequencies. Software Receiver Design Johnson/Sethares/Klein 17 / 24

Matched Filter (cont d) With spectrally flat channel noise the SNR-maximizing receive filter impulse response is the time-reversal of that of the pulse shape. The Fourier transform of the autocorrelation function of w(t) 1 T/2 R w (τ) = lim w(t)w(t+τ)dt T T T/2 equals the power spectral density of w(t) W T (f) 2 P w (f) = lim T T where W T (f) is the Fourier transform of the truncated w(t) { w(t) T/2 < t < T/2 w T (t) = otherwise Software Receiver Design Johnson/Sethares/Klein 18 / 24

Matched Filter (cont d) From (E.4), the power spectral density of the output y of a linear filter h with input u is P y (f) = P u (f) H(f) 2 Thus, with noise n having a flat power spectral density P w (f) = P n (f) H R (f) 2 = η H R (f) 2 From (E.2), total power in w is P w = f= P w (f)df With our objective of choosing h R (t) to maximize the power of the signal v(t) at a specific time t = τ, i.e. v 2 (τ), relative to the total power of w(t), we now need to compute v 2 (τ). Software Receiver Design Johnson/Sethares/Klein 19 / 24

Matched Filter (cont d) Turning to calculation of v 2, from (A.16) v(τ) = where V(f) = H R (f)g(f), so v 2 (τ) = f= V(f)e j2πfτ df H R (f)g(f)e j2πfτ df 2 The quantity to be maximized is v 2 (τ) = H R(f)G(f)e j2πfτ df 2 P w η H R(f) 2 df Schwarz s inequality (A.57) is a(x)b(x)dx 2 { } dx}{ a(x) 2 b(x) 2 dx and equality occurs only when a(x) = kb (x) where superscript denotes complex conjugation. Software Receiver Design Johnson/Sethares/Klein 2 / 24

Matched Filter (cont d) By Schwarz s inequality ( )( v 2 (τ) H R(f) 2 df G(f)ej2πfτ df) 2 P w η H R(f) 2 df with the maximum of v 2 (τ)/p w when H R (f) = k(g(f)e j2πfτ ) Combining the symmetry property (A.35) for real w F 1 {W ( f)} = w (t) F 1 {W (f)} = w ( t) and the time shift property (A.38) yields F 1 {W(f)e j2πft d } = w(t T d ) F 1 {(W(f)e j2πft d ) } = w ( (t T d )) = w (T d t) Software Receiver Design Johnson/Sethares/Klein 21 / 24

Matched Filter (cont d) Thus, when g(t) is real Example: F 1 {k(g(f)e j2πfτ ) } = kg (τ t) = kg(τ t) Minimum τ for causality of matched filter is pulse width for pulse initiated at t =. Software Receiver Design Johnson/Sethares/Klein 22 / 24

Matched Nyquist Transmit and Receive Filter Combinations A preferred receive filter impulse response (in the absence of channel ISI but with broadband channel noise) (i) will match the reversed impulse response of the transmitter pulse shape and (ii) when convolved with the transmitter pulse shape will form a Nyquist pulse. Want convolution of candidate pulse shape g(t) and its matched filter g(t τ) to equal even symmetric Nyquist pulse p(t). Since convolution of two even symmetric pulse shapes is even symmetric, presume g(t) is even symmetric, so with particular τ, g(t) = g(τ t). Objective becomes p(t) = g(t) g(t) P(f) = G 2 (f) Software Receiver Design Johnson/Sethares/Klein 23 / 24

Matched... Combinations (cont d) So, choose G(f) = P(f) g(t) = F 1 { P(f)} For example, consider the square-root raised cosine (SRRC) v(t) = 1 sin(π(1 α)t/t)+(4αt/t)cos(π(1+α)t/t) T (πt/t)(1 (4αt/T) 2 ) for t, t ± T 4α 1 T (1 α+(4α/π)) for t = [( ) ( α 2T 1+ 2 π sin π ) ( 4α + 1 2 π for t = ± T 4α ) cos ( π 4α which has a magnitude spectrum the square of which equals the magnitude spectrum of a raised cosine. The square root raised cosine is the most commonly used pulse in bandwidth constrained communication systems. NEXT... We concoct various timing (aka clock) recovery schemes. Software Receiver Design Johnson/Sethares/Klein 24 / 24 )]