5 Signal Design for Bandlimited Channels



Similar documents
Implementation of Digital Signal Processing: Some Background on GFSK Modulation

Appendix D Digital Modulation and GMSK

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

Digital Transmission (Line Coding)

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

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

T = 1 f. Phase. Measure of relative position in time within a single period of a signal For a periodic signal f(t), phase is fractional part t p


MODULATION Systems (part 1)

Time and Frequency Domain Equalization

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

2 The wireless channel

Lecture 8 ELE 301: Signals and Systems

Sampling Theorem Notes. Recall: That a time sampled signal is like taking a snap shot or picture of signal periodically.

Non-Data Aided Carrier Offset Compensation for SDR Implementation

QAM Demodulation. Performance Conclusion. o o o o o. (Nyquist shaping, Clock & Carrier Recovery, AGC, Adaptive Equaliser) o o. Wireless Communications

ELE745 Assignment and Lab Manual

Lezione 6 Communications Blockset

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

Experiment 3: Double Sideband Modulation (DSB)

EECC694 - Shaaban. Transmission Channel

Digital Communications

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

Adaptive Equalization of binary encoded signals Using LMS Algorithm

Digital Baseband Modulation

NRZ Bandwidth - HF Cutoff vs. SNR

Lecture 3: Signaling and Clock Recovery. CSE 123: Computer Networks Stefan Savage

Example/ an analog signal f ( t) ) is sample by f s = 5000 Hz draw the sampling signal spectrum. Calculate min. sampling frequency.

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

Digital Transmission of Analog Data: PCM and Delta Modulation

How To Understand The Nyquist Sampling Theorem

A WEB BASED TRAINING MODULE FOR TEACHING DIGITAL COMMUNICATIONS

From Fundamentals of Digital Communication Copyright by Upamanyu Madhow,

Mobile Communications Chapter 2: Wireless Transmission

BSEE Degree Plan Bachelor of Science in Electrical Engineering:

Public Switched Telephone System

SIGNAL PROCESSING & SIMULATION NEWSLETTER

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

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

4 Digital Video Signal According to ITU-BT.R.601 (CCIR 601) 43

Voice---is analog in character and moves in the form of waves. 3-important wave-characteristics:

The Effect of Network Cabling on Bit Error Rate Performance. By Paul Kish NORDX/CDT

INTRODUCTION TO COMMUNICATION SYSTEMS AND TRANSMISSION MEDIA

Introduction to Modem Design. Paolo Prandoni, LCAV - EPFL

Course Curriculum for Master Degree in Electrical Engineering/Wireless Communications

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

(2) (3) (4) (5) 3 J. M. Whittaker, Interpolatory Function Theory, Cambridge Tracts

Data Transmission. Data Communications Model. CSE 3461 / 5461: Computer Networking & Internet Technologies. Presentation B

MSB MODULATION DOUBLES CABLE TV CAPACITY Harold R. Walker and Bohdan Stryzak Pegasus Data Systems ( 5/12/06) pegasusdat@aol.com

RECOMMENDATION ITU-R F.1101 * Characteristics of digital fixed wireless systems below about 17 GHz

ISI Mitigation in Image Data for Wireless Wideband Communications Receivers using Adjustment of Estimated Flat Fading Errors

Module: Digital Communications. Experiment 784. DSL Transmission. Institut für Nachrichtentechnik E-8 Technische Universität Hamburg-Harburg

CONVOLUTION Digital Signal Processing

MIMO CHANNEL CAPACITY

IN current film media, the increase in areal density has

The continuous and discrete Fourier transforms

Introduction to FM-Stereo-RDS Modulation

1. (Ungraded) A noiseless 2-kHz channel is sampled every 5 ms. What is the maximum data rate?

Chapter 8 - Power Density Spectrum

Aliasing, Image Sampling and Reconstruction

Introduction to IQ-demodulation of RF-data

ANALYZER BASICS WHAT IS AN FFT SPECTRUM ANALYZER? 2-1

6.976 High Speed Communication Circuits and Systems Lecture 1 Overview of Course

ELT Advanced Course in Digital Transmission. Lecture 1

How To Understand The Theory Of Time Division Duplexing

Introduction to Digital Subscriber s Line (DSL)

DVB-T. The echo performance of. receivers. Theory of echo tolerance. Ranulph Poole BBC Research and Development

Simulation of Wireless Fading Channels

RADIO FREQUENCY INTERFERENCE AND CAPACITY REDUCTION IN DSL

Modulation and Demodulation

PAPR and Bandwidth Analysis of SISO-OFDM/WOFDM and MIMO OFDM/WOFDM (Wimax) for Multi-Path Fading Channels

CDMA Performance under Fading Channel

Electronic Communications Committee (ECC) within the European Conference of Postal and Telecommunications Administrations (CEPT)

How To Understand The Discrete Fourier Transform

APPLICATION NOTE. RF System Architecture Considerations ATAN0014. Description

Principles of Digital Communication

RF SYSTEM DESIGN OF TRANSCEIVERS FOR WIRELESS COMMUNICATIONS

Adjacent Channel Interference. Adaptive Modulation and Coding. Advanced Mobile Phone System. Automatic Repeat Request. Additive White Gaussian Noise

Broadcast digital subscriber lines using discrete multitone for broadband access

ADSL Physical Layer. 6.1 Introduction

TTT4110 Information and Signal Theory Solution to exam

Implementing Digital Wireless Systems. And an FCC update

CDMA TECHNOLOGY. Brief Working of CDMA

A Performance Study of Wireless Broadband Access (WiMAX)

Sampling and Interpolation. Yao Wang Polytechnic University, Brooklyn, NY11201

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

Vector Signal Analyzer FSQ-K70

On-Line Diagnosis using Orthogonal Multi-Tone Time Domain Reflectometry in a Lossy Cable

AN Application Note: FCC Regulations for ISM Band Devices: MHz. FCC Regulations for ISM Band Devices: MHz

SC-FDMA and LTE Uplink Physical Layer Design

1995 Mixed-Signal Products SLAA013

chapter Introduction to Digital Signal Processing and Digital Filtering 1.1 Introduction 1.2 Historical Perspective

RF Measurements Using a Modular Digitizer

Transcription:

225 5 Signal Design for Bandlimited Channels So far, we have not imposed any bandwidth constraints on the transmitted passband signal, or equivalently, on the transmitted baseband signal s b (t) I[k]g T (t kt), k where we assume a linear modulation (PAM, PSK, or QAM), and I[k] and g T (t) denote the transmit symbols and the transmit pulse, respectively. In practice, however, due to the properties of the transmission medium (e.g. cable or multipath propagation in wireless), the underlying transmission channel is bandlimited. If the bandlimited character of the channel is not taken into account in the signal design at the transmitter, the received signal will be (linearly) distorted. In this chapter, we design transmit pulse shapes g T (t) that guarantee that s b (t) occupies only a certain finite bandwidth W. At the same time, these pulse shapes allow ML symbol by symbol detection at the receiver.

226 5. Characterization of Bandlimited Channels Many communication channels can be modeled as linear filters with (equivalent baseband) impulse response c(t) and frequency response C(f) F{c(t)}. z(t) s b (t) c(t) y b (t) The received signal is given by y b (t) s b (τ)c(t τ) dτ + z(t), where z(t) denotes complex Gaussian noise with power spectral density N 0. We assume that the channel is ideally bandlimited, i.e., C(f) 0, f > W. C(f) W W f

227 Within the interval f W, the channel is characterized by C(f) C(f) e jθ(f) with amplitude response C(f) and phase response Θ(f). If S b (f) F{s b (t)} is non zero only in the interval f W, then s b (t) is not distorted if and only if. C(f) A, i.e., the amplitude response is constant for f W. 2. Θ(f) 2πfτ 0, i.e., the phase response is linear in f, where τ 0 is the delay. In this case, the received signal is given by y b (t) As b (t τ 0 ) + z(t). As far as s b (t) is concerned, the impulse response of the channel can be modeled as c(t) Aδ(t τ 0 ). If the above conditions are not fulfilled, the channel linearly distorts the transmitted signal and an equalizer is necessary at the receiver.

228 5.2 Signal Design for Bandlimited Channels We assume an ideal, bandlimited channel, i.e., {, f W C(f) 0, f > W. The transmit signal is s b (t) k I[k]g T (t kt). In order to avoid distortion, we assume G T (f) F{g T (t)} 0, f > W. This implies that the received signal is given by y b (t) s b (τ)c(t τ) dτ + z(t) s b (t) + z(t) I[k]g T (t kt) + z(t). k In order to limit the noise power in the demodulated signal, y b (t) is usually filtered with a filter g R (t). Thereby, g R (t) can be e.g. a lowpass filter or the optimum matched filter. The filtered received signal is r b (t) g R (t) y b (t) I[k]x(t kt) + ν(t) k

229 where denotes convolution, and we use the definitions x(t) g T (t) g R (t) g T (τ)g R (t τ) dτ and ν(t) g R (t) z(t) z(t) s b (t) c(t) y b (t) g R (t) r b (t) Now, we sample r b (t) at times t kt +t 0, k...,, 0,,..., where t 0 is an arbitrary delay. For simplicity, we assume t 0 0 in the following and obtain r b [k] r b (kt) κ κ I[κ] x(kt κt) } {{ } x[k κ] I[κ]x[k κ] + z[k] +ν(kt) } {{ } z[k]

230 We can rewrite r b [k] as r b [k] x[0] I[k] + x[0] κ κ k I[κ]x[k κ] + z[k], where the term κ κ k I[κ]x[k κ] represents so called intersymbol interference (ISI). Since x[0] only depends on the amplitude of g R (t) and g T (t), respectively, for simplicity we assume x[0] in the following. Ideally, we would like to have which implies r b [k] I[k] + z[k], κ κ k i.e., the transmission is ISI free. I[κ]x[k κ] 0, Problem Statement How do we design g T (t) and g R (t) to guarantee ISI free transmission?

23 Solution: The Nyquist Criterion Since x(t) g R (t) g T (t) is valid, the Fourier transform of x(t) can be expressed as X(f) G T (f) G R (f), with G T (f) F{g T (t)} and G R (f) F{g R (t)}. For ISI free transmission, x(t) has to have the property x(kt) x[k] {, k 0 0, k 0 () The Nyquist Criterion According to the Nyquist Criterion, condition () is fulfilled if and only if m X ( f + m T ) T is true. This means summing up all spectra that can be obtained by shifting X(f) by multiples of /T results in a constant.

232 Proof: x(t) may be expressed as x(t) X(f)e j2πft df. Therefore, x[k] x(kt) can be written as x[k] X(f)e j2πfkt df (2m+)/() m (2m )/() /() m /() /() /() /() m X(f)e j2πfkt df X(f + m/t)e j2π(f +m/t)kt df X(f + m/t) e j2πf kt df } {{ } B(f ) B(f)e j2πfkt df (2) Since /() B(f) m X(f + m/t)

233 is periodic with period /T, it can be expressed as a Fourier series B(f) b[k]e j2πfkt (3) k where the Fourier series coefficients b[k] are given by b[k] T /() B(f)e j2πfkt df. (4) /() From (2) and (4) we observe that b[k] Tx( kt). Therefore, () holds if and only if b[k] { T, k 0 0, k 0. However, in this case (3) yields B(f) T, which means X(f + m/t) T. m This completes the proof.

234 The Nyquist criterion specifies the necessary and sufficient condition that has to be fulfilled by the spectrum X(f) of x(t) for ISI free transmission. Pulse shapes x(t) that satisfy the Nyquist criterion are referred to as Nyquist pulses. In the following, we discuss three different cases for the symbol duration T. In particular, we consider T < /(2W), T /(2W), and T > /(2W), respectively, where W is the bandwidth of the ideally bandlimited channel.. T < /(2W) If the symbol duration T is smaller than /(2W), we get obviously and B(f) > W m consists of non overlapping pulses. X(f + m/t) B(f) W W f We observe that in this case the condition B(f) T cannot be fulfilled. Therefore, ISI free transmission is not possible.

235 2. T /(2W) If the symbol duration T is equal to /(2W), we get W and B(f) T is achieved for X(f) { T, f W 0, f > W. This corresponds to x(t) sin( π t T π t T ) B(f) T f T /(2W) is also called the Nyquist rate and is the fastest rate for which ISI free transmission is possible. In practice, however, this choice is usually not preferred since x(t) decays very slowly ( /t) and therefore, time synchronization is problematic.

236 3. T > /(2W) In this case, we have Example: < W and B(f) consists of overlapping, shifted replica of X(f). ISI free transmission is possible if X(f) is chosen properly. X(f) T T 2 f B(f) T T 2 f

237 The bandwidth occupied beyond the Nyquist bandwidth /() is referred to as the excess bandwidth. In practice, Nyquist pulses with raised cosine spectra are popular T, ( ( [ ])) 0 f β T πt X(f) 2 + cos β f β β +β, < f 0, f > +β where β, 0 β, is the roll off factor. The inverse Fourier transform of X(f) yields x(t) sin(πt/t) πt/t cos(πβt/t) 4β 2 t 2 /T 2. For β 0, x(t) reduces to x(t) sin(πt/t)/(πt/t). For β > 0, x(t) decays as /t 3. This fast decay is desirable for time synchronization. 0.9 0.8 0.7 0.6 X(f)/T 0.5 0.4 0.3 β β 0.35 0.2 0. β 0 0 0.8 0.6 0.4 0.2 0 0.2 0.4 0.6 0.8 ft

238 0.8 0.6 x(t) 0.4 0.2 β 0.35 0 0.2 0.4 4 3 2 0 2 3 4 t/t β β 0

239 Nyquist Filters The spectrum of x(t) is given by G T (f) G R (f) X(f) ISI free transmission is of course possible for any choice of G T (f) and G R (f) as long as X(f) fulfills the Nyquist criterion. However, the SNR maximizing optimum choice is G T (f) G(f) G R (f) αg (f), i.e., g R (t) is matched to g T (t). α is a constant. In that case, X(f) is given by X(f) α G(f) 2 and consequently, G(f) can be expressed as G(f) α X(f). G(f) is referred to as Nyquist Filter. In practice, a delay τ 0 may be added to G T (f) and/or G R (f) to make them causal filters in order to ensure physical realizability of the filters.

240 5.3 Discrete Time Channel Model for ISI free Transmission Continuous Time Channel Model z(t) I[k] g T (t) c(t) g R (t) r b (t) kt r b [k] g T (t) and g R (t) are Nyquist Impulses that are matched to each other. Equivalent Discrete Time Channel Model z[k] I[k] Eg r b [k] Proof: z[k] is a discrete time AWGN process with variance σ 2 Z N 0. Signal Component The overall channel is given by x[k] g T (t) c(t) g R (t) g T (t) g R (t), tkt tkt

24 where we have used the fact that the channel acts as an ideal lowpass filter. We assume g R (t) g(t) g T (t) g ( t), Eg where g(t) is a Nyquist Impulse, and E g is given by E g g(t) 2 dt Consequently, x[k] is given by x[k] g(t) g ( t) Eg tkt g(t) g ( t) δ[k] Eg t0 Eg E g δ[k] E g δ[k] Noise Component z(t) is a complex AWGN process with power spectral density

242 Φ ZZ (f) N 0. z[k] is given by z[k] g R (t) z(t) tkt g ( t) z(t) Eg Eg Mean E{z[k]} E Eg Eg tkt z(τ)g (kt + τ) dτ z(τ)g (kt + τ) dτ E{z(τ)}g (kt + τ) dτ 0

243 ACF φ ZZ [λ] E{z[k + λ]z [k]} E g N 0 E g N 0 E g E g δ[λ] N 0 δ[λ] E{z(τ )z (τ 2 )} g } {{ } ([k + λ]t + τ ) N 0 δ(τ τ 2 ) g(kt + τ 2 ) dτ dτ 2 g ([k + λ]t + τ )g(kt + τ ) dτ This shows that z[k] is a discrete time AWGN process with variance σ 2 Z N 0 and the proof is complete. The discrete time, demodulated received signal can be modeled as r b [k] E g I[k] + z[k]. This means the demodulated signal is identical to the demodulated signal obtained for time limited transmit pulses (see Chapter 3 and 4). Therefore, the optimum detection strategies developed in Chapter 4 can be also applied for finite bandwidth transmission as long as the Nyquist criterion is fulfilled.