IEEE 802.3ap Task Force Ottawa Sept 27-29, 2004
|
|
- Rafe Horn
- 5 years ago
- Views:
Transcription
1 Edge-Equalized NRZ and Duobinary IEEE 82.3ap Task Force Ottawa Sept 27-29, 24 Brian Brunn, Xilinx
2 Intro It appears the equalization algorithm for EE-NRZ and Duobinary are the same. Both want to zero-force the composite pulse response to Duobinary is perceived as generally desiring a null at 5GHz. With duobinary we can take advantage of the roll-off in the channel but when we use symbol-spaced FIR equalization, it is hard to separate out the equalization from the duobinary function. The sampled sequence.5.5 has a null at 5GHz. This presents two questions: How can a 1Gbps signal have a null at 5GHz and be NRZ detectable? What about the 11 pattern? Can a 1Gbps signal have a significant 5GHz component and still be DB detectable with no ISI at the bit center? ISI is important not only at the bit center. EE-NRZ and Duobinary 2
3 Hypothesis Perhaps there something else besides just zero forcing to.5.5? If we restrict ourselves to symbol-spaced FIR filtering where UI = Tsample = 1ps then 5GHz = π in the z-domain. Equalizer frequency response symmetric about 5GHz due to aliasing. No fractional spaced taps. FIR filter design requires a priori selection of a symmetry type. Odd-symmetric FIR systems can not have a null at π (not good for low-pass) Even-symmetric FIR systems always have a null at π (can t be high-pass). So this suggests odd-symmetric FIR filtering may be good for EE- NRZ and even-symmetric FIR filtering may be good for duobinary. Lets try the two different FIR types and perform ZFE to produce a.5.5 composite pulse response. EE-NRZ and Duobinary 3
4 Analysis steps taken Start with a 1Gbps system that results in a pulse response that is a gaussian pulse with the 5GHz -21.4dB Using odd-sense FIR symmetry for EE-NRZ equalization, generate MSE FIR tap coefficients to meet the.5.5 criteria on the composite pulse response. Repeat for even-sense FIR symmetry for duobinary equalization. Plot frequency and eye diagrams. EE-NRZ and Duobinary 4
5 System Pulse Response time [ps] Time -1 ( ) := e ytσ, Y ω, σ t σ 2 ( ) := π ( σ ) 2 Frequency σ := exp 1 4 ω2 ( σ ) 2 ( ) 2 log Y ( ω, σ ) := ( ) Y db ω, σ Yσ, -2-3 ( ) = Y db 2 π 5 1 9, Frequency [GHz] EE-NRZ and Duobinary 5
6 EE-NRZ composite pulse generation tap() tap(+1) tap(-1) tap(+2) tap(-2) EE E-1-3.E-1-2.E-1-1.E-1.E+ 1.E-1 2.E-1 3.E-1 4.E-1 EE-NRZ and Duobinary 6
7 Duobinary composite pulse generation tap(+3.5) tap(+2.5) tap(+1.5) tap(+) tap(-) tap(-1.5) tap(-2.5) tap(-3.5) Duo E-1-3.E-1-2.E-1-1.E-1.E+ 1.E-1 2.E-1 3.E-1 4.E-1 EE-NRZ and Duobinary 7
8 Equalizer Freq response overlay Duobinary ( ( ( )) ) 2 log H_even exp 1j 2 π Freq k T ( ( ( )) ) 2 log H_odd exp 1j 2 π Freq k T EE-NRZ Freq k 11 1 EE-NRZ and Duobinary 8
9 Composite pulse response overlay Zeroforcing criteria met for both cases DB EE EE Duo E-1-3.E-1-2.E-1-1.E-1.E+ 1.E-1 2.E-1 3.E-1 4.E-1 EE-NRZ and Duobinary 9
10 EE-NRZ eye diagram psec EE-NRZ and Duobinary 1
11 Duobinary eye diagram psec EE-NRZ and Duobinary 11
12 Duobinary eye scaled for equal Tx power psec EE-NRZ and Duobinary 12
13 EE-NRZ and Duobinary comparison Scaled for equal TX power psec EE-NRZ has an even larger 3-level eye psec EE-NRZ and Duobinary 13
14 Conclusion Using a channel with a given pulse response, two ways to construct symbol-spaced FIR filtered signaling that results in a 3- level constellation were shown. Both satisfy the.5.5 minimum squared error criteria. Demonstrated two resulting and distinct composite pulse responses satisfying the same error criteria and offering insight into the apparent NRZ/null at 5GHz paradox. In one implementation (odd), the signal is both 2-level and 3-level detectable. This EE-NRZ. In the other implementation (even), the signal is only 3-level detectable. It has a null at 5GHz. When scaled for equal TX power, the 3-level eye opening is larger for the odd implementation. Optimal FIR equalized NRZ and duobinary receivers may want the exact same tap settings. EE-NRZ and Duobinary 14
EE5713 : Advanced Digital Communications
EE5713 : Advanced Digital Communications Week 12, 13: Inter Symbol Interference (ISI) Nyquist Criteria for ISI Pulse Shaping and Raised-Cosine Filter Eye Pattern Equalization (On Board) 20-May-15 Muhammad
More informationLecture 5b: Line Codes
Lecture 5b: Line Codes Dr. Mohammed Hawa Electrical Engineering Department University of Jordan EE421: Communications I Digitization Sampling (discrete analog signal). Quantization (quantized discrete
More informationEs e j4φ +4N n. 16 KE s /N 0. σ 2ˆφ4 1 γ s. p(φ e )= exp 1 ( 2πσ φ b cos N 2 φ e 0
Problem 6.15 : he received signal-plus-noise vector at the output of the matched filter may be represented as (see (5-2-63) for example) : r n = E s e j(θn φ) + N n where θ n =0,π/2,π,3π/2 for QPSK, and
More informationADAPTIVE EQUALIZATION AT MULTI-GHZ DATARATES
ADAPTIVE EQUALIZATION AT MULTI-GHZ DATARATES Department of Electrical Engineering Indian Institute of Technology, Madras 1st February 2007 Outline Introduction. Approaches to electronic mitigation - ADC
More informationTHE IMPACT POLARIZATION MODE DISPERSION OPTICAL DUOBINARY TRANSMISSION
THE IMPACT of POLARIZATION MODE DISPERSION on OPTICAL DUOBINARY TRANSMISSION A. Carena, V. Curri, R. Gaudino, P. Poggiolini Optical Communications Group - Politecnico di Torino Torino - ITALY OptCom@polito.it
More informationSerDes_Channel_Impulse_Modeling_with_Rambus
SerDes_Channel_Impulse_Modeling_with_Rambus Author: John Baprawski; John Baprawski Inc. (JB) Email: John.baprawski@gmail.com Web sites: https://www.johnbaprawski.com; https://www.serdesdesign.com Date:
More informationEE290C Spring Motivation. Lecture 6: Link Performance Analysis. Elad Alon Dept. of EECS. Does eqn. above predict everything? EE290C Lecture 5 2
EE29C Spring 2 Lecture 6: Link Performance Analysis Elad Alon Dept. of EECS Motivation V in, ampl Voff BER = 2 erfc 2σ noise Does eqn. above predict everything? EE29C Lecture 5 2 Traditional Approach Borrowed
More informationWeiyao Lin. Shanghai Jiao Tong University. Chapter 5: Digital Transmission through Baseband slchannels Textbook: Ch
Principles of Communications Weiyao Lin Shanghai Jiao Tong University Chapter 5: Digital Transmission through Baseband slchannels Textbook: Ch 10.1-10.5 2009/2010 Meixia Tao @ SJTU 1 Topics to be Covered
More informationPrinciples of Communications
Principles of Communications Chapter V: Representation and Transmission of Baseband Digital Signal Yongchao Wang Email: ychwang@mail.xidian.edu.cn Xidian University State Key Lab. on ISN November 18, 2012
More information10GBASE-KR Transmitter Compliance Methodology Proposal. Robert Brink Agere Systems May 13, 2005
0GBASE-KR Transmitter Compliance Methodology Proposal Robert Brink Agere Systems May 3, 2005 Scope and Purpose Deficiencies of existing transmit template compliance methods are discussed. A proposal for
More informationPrinciples of Communications Lecture 8: Baseband Communication Systems. Chih-Wei Liu 劉志尉 National Chiao Tung University
Principles of Communications Lecture 8: Baseband Communication Systems Chih-Wei Liu 劉志尉 National Chiao Tung University cwliu@twins.ee.nctu.edu.tw Outlines Introduction Line codes Effects of filtering Pulse
More informationPolarization division multiplexing system quality in the presence of polarization effects
Opt Quant Electron (2009) 41:997 1006 DOI 10.1007/s11082-010-9412-0 Polarization division multiplexing system quality in the presence of polarization effects Krzysztof Perlicki Received: 6 January 2010
More informationDigital Baseband Systems. Reference: Digital Communications John G. Proakis
Digital Baseband Systems Reference: Digital Communications John G. Proais Baseband Pulse Transmission Baseband digital signals - signals whose spectrum extend down to or near zero frequency. Model of the
More informationConsider a 2-D constellation, suppose that basis signals =cosine and sine. Each constellation symbol corresponds to a vector with two real components
TUTORIAL ON DIGITAL MODULATIONS Part 3: 4-PSK [2--26] Roberto Garello, Politecnico di Torino Free download (for personal use only) at: www.tlc.polito.it/garello Quadrature modulation Consider a 2-D constellation,
More informationSummary: ISI. No ISI condition in time. II Nyquist theorem. Ideal low pass filter. Raised cosine filters. TX filters
UORIAL ON DIGIAL MODULAIONS Part 7: Intersymbol interference [last modified: 200--23] Roberto Garello, Politecnico di orino Free download at: www.tlc.polito.it/garello (personal use only) Part 7: Intersymbol
More informationSimilarities of PMD and DMD for 10Gbps Equalization
Similarities of PMD and DMD for 10Gbps Equalization Moe Win Jack Winters win/jhw@research.att.com AT&T Labs-Research (Some viewgraphs and results curtesy of Julien Porrier) Outline Polarization Mode Dispersion
More informationAdaptive Polarization Mode Dispersion Compensation at 40Gb/s with Integrated Optical Finite Impulse Response (FIR) Filters
Adaptive Polarization Mode Dispersion Compensation at 40Gb/s with Integrated Optical Finite Impulse Response (FIR) Filters Marc Bohn, Werner Rosenkranz Chair for Communications, University of Kiel, Kaiserstr.
More informationRevision of Lecture 4
Revision of Lecture 4 We have discussed all basic components of MODEM Pulse shaping Tx/Rx filter pair Modulator/demodulator Bits map symbols Discussions assume ideal channel, and for dispersive channel
More informationSI/PI PCB Design Considerations for Thermal
SI/PI PCB Design Considerations for Thermal HEESOO LEE Lead Application Developer PIPro Power Integrity Professional Agenda Thermal effects on Signal Integrity and Power Integrity Case study Conclusion
More informationComputation of Bit-Error Rate of Coherent and Non-Coherent Detection M-Ary PSK With Gray Code in BFWA Systems
Computation of Bit-Error Rate of Coherent and Non-Coherent Detection M-Ary PSK With Gray Code in BFWA Systems Department of Electrical Engineering, College of Engineering, Basrah University Basrah Iraq,
More informationDecision-Point Signal to Noise Ratio (SNR)
Decision-Point Signal to Noise Ratio (SNR) Receiver Decision ^ SNR E E e y z Matched Filter Bound error signal at input to decision device Performance upper-bound on ISI channels Achieved on memoryless
More informationLine Codes and Pulse Shaping Review. Intersymbol interference (ISI) Pulse shaping to reduce ISI Embracing ISI
Line Codes and Pulse Shaping Review Line codes Pulse width and polarity Power spectral density Intersymbol interference (ISI) Pulse shaping to reduce ISI Embracing ISI Line Code Examples (review) on-off
More informationECEN689: Special Topics in High-Speed Links Circuits and Systems Spring 2012
ECEN689: pecial Topics in High-peed Links Circuits and ystems pring 01 Lecture 3: Time-Domain Reflectometry & -Parameter Channel Models am Palermo Analog & Mixed-ignal Center Texas A&M University Announcements
More informationSummary: SER formulation. Binary antipodal constellation. Generic binary constellation. Constellation gain. 2D constellations
TUTORIAL ON DIGITAL MODULATIONS Part 8a: Error probability A [2011-01-07] 07] Roberto Garello, Politecnico di Torino Free download (for personal use only) at: www.tlc.polito.it/garello 1 Part 8a: Error
More informationGEORGIA INSTITUTE OF TECHNOLOGY SCHOOL OF ELECTRICAL AND COMPUTER ENGINEERING Final Examination - Fall 2015 EE 4601: Communication Systems
GEORGIA INSTITUTE OF TECHNOLOGY SCHOOL OF ELECTRICAL AND COMPUTER ENGINEERING Final Examination - Fall 2015 EE 4601: Communication Systems Aids Allowed: 2 8 1/2 X11 crib sheets, calculator DATE: Tuesday
More information1. 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
TUTORIAL ON DIGITAL MODULATIONS Part 14: m-psk [last modified: 2010-11-25] Roerto Garello, Politecnico di Torino Free download at: www.tlc.polito.it/garello (personal use only) 1 m-psk modulations 1. Band-pass
More informationa) Find the compact (i.e. smallest) basis set required to ensure sufficient statistics.
Digital Modulation and Coding Tutorial-1 1. Consider the signal set shown below in Fig.1 a) Find the compact (i.e. smallest) basis set required to ensure sufficient statistics. b) What is the minimum Euclidean
More informationSignal Processing for Digital Data Storage (11)
Outline Signal Processing for Digital Data Storage (11) Assist.Prof. Piya Kovintavewat, Ph.D. Data Storage Technology Research Unit Nahon Pathom Rajabhat University Partial-Response Maximum-Lielihood (PRML)
More informationA Family of Nyquist Filters Based on Generalized Raised-Cosine Spectra
Proc. Biennial Symp. Commun. (Kingston, Ont.), pp. 3-35, June 99 A Family of Nyquist Filters Based on Generalized Raised-Cosine Spectra Nader Sheikholeslami Peter Kabal Department of Electrical Engineering
More informationMethod for analytically calculating BER (bit error rate) in presence of non-linearity. Gaurav Malhotra Xilinx
Method for analytically calculating BER (bit error rate) in presence of non-linearity Gaurav Malhotra Xilinx Outline Review existing methodology for calculating BER based on linear system analysis. Link
More informationToday. ESE 531: Digital Signal Processing. IIR Filter Design. Impulse Invariance. Impulse Invariance. Impulse Invariance. ω < π.
Today ESE 53: Digital Signal Processing! IIR Filter Design " Lec 8: March 30, 207 IIR Filters and Adaptive Filters " Bilinear Transformation! Transformation of DT Filters! Adaptive Filters! LMS Algorithm
More informationEE538 Digital Signal Processing I Session 13 Exam 1 Live: Wed., Sept. 18, Cover Sheet
EE538 Digital Signal Processing I Session 3 Exam Live: Wed., Sept. 8, 00 Cover Sheet Test Duration: 50 minutes. Coverage: Sessions -0. Open Book but Closed Notes. Calculators not allowed. This test contains
More informationDIGITAL COMMUNICATIONS. IAGlover and P M Grant. Prentice Hall 1997 PROBLEM SOLUTIONS CHAPTER 6
DIGITAL COMMUNICATIONS IAGlover and P M Grant Prentice Hall 997 PROBLEM SOLUTIONS CHAPTER 6 6. P e erf V σ erf. 5 +. 5 0.705 [ erf (. 009)] [ 0. 999 979 ]. 0 0 5 The optimum DC level is zero. For equiprobable
More informationPreliminary Studies on DFE Error Propagation, Precoding, and their Impact on KP4 FEC Performance for PAM4 Signaling Systems
Preliminary Studies on DFE Error Propagation, Precoding, and their Impact on KP4 FEC Performance for PAM4 Signaling Systems Geoff Zhang September, 2018 Outline 1/(1+D) precoding for PAM4 link systems 1/(1+D)
More information14 Gb/s AC Coupled Receiver in 90 nm CMOS. Masum Hossain & Tony Chan Carusone University of Toronto
14 Gb/s AC Coupled Receiver in 90 nm CMOS Masum Hossain & Tony Chan Carusone University of Toronto masum@eecg.utoronto.ca OUTLINE Chip-to-Chip link overview AC interconnects Link modelling ISI & sensitivity
More informationDigital Communications
Digital Communications Chapter 9 Digital Communications Through Band-Limited Channels Po-Ning Chen, Professor Institute of Communications Engineering National Chiao-Tung University, Taiwan Digital Communications:
More informationMath 231E, Lecture 25. Integral Test and Estimating Sums
Math 23E, Lecture 25. Integral Test and Estimating Sums Integral Test The definition of determining whether the sum n= a n converges is:. Compute the partial sums s n = a k, k= 2. Check that s n is a convergent
More informationRADIO SYSTEMS ETIN15. Lecture no: Equalization. Ove Edfors, Department of Electrical and Information Technology
RADIO SYSTEMS ETIN15 Lecture no: 8 Equalization Ove Edfors, Department of Electrical and Information Technology Ove.Edfors@eit.lth.se Contents Inter-symbol interference Linear equalizers Decision-feedback
More informationLeistungsfähigkeit von elektronischen Entzerrer in hochbitratigen optischen Übertragungsystemen. S. Otte, W. Rosenkranz. chair for communications,
Leistungsfähigkeit von elektronischen Entzerrer in hochbitratigen optischen Übertragungsystemen S. Otte, W. Rosenkranz chair for communications, Sven Otte, DFG-Kolloquium, 6. 11. 001, 1 Outline 1. Motivation.
More informationEE 661: Modulation Theory Solutions to Homework 6
EE 66: Modulation Theory Solutions to Homework 6. Solution to problem. a) Binary PAM: Since 2W = 4 KHz and β = 0.5, the minimum T is the solution to (+β)/(2t ) = W = 2 0 3 Hz. Thus, we have the maximum
More informationADAPTIVE FILTER ALGORITHMS. Prepared by Deepa.T, Asst.Prof. /TCE
ADAPTIVE FILTER ALGORITHMS Prepared by Deepa.T, Asst.Prof. /TCE Equalization Techniques Fig.3 Classification of equalizers Equalizer Techniques Linear transversal equalizer (LTE, made up of tapped delay
More informationChapter 7: IIR Filter Design Techniques
IUST-EE Chapter 7: IIR Filter Design Techniques Contents Performance Specifications Pole-Zero Placement Method Impulse Invariant Method Bilinear Transformation Classical Analog Filters DSP-Shokouhi Advantages
More informationNotes on a posteriori probability (APP) metrics for LDPC
Notes on a posteriori probability (APP) metrics for LDPC IEEE 802.3an Task Force November, 2004 Raju Hormis, Xiaodong Wang Columbia University, NY e-mail: raju@ee.columbia.edu Outline Section 55.3.11.3
More informationAccurate Calculation of Bit Error Rates in Optical Fiber Communications Systems
Accurate Calculation of Bit Error Rates in Optical Fiber Communications Systems presented by Curtis R. Menyuk 1 Contributors Ronald Holzlöhner Ivan T. Lima, Jr. Amitkumar Mahadevan Brian S. Marks Joel
More informationOversampling Converters
Oversampling Converters David Johns and Ken Martin (johns@eecg.toronto.edu) (martin@eecg.toronto.edu) slide 1 of 56 Motivation Popular approach for medium-to-low speed A/D and D/A applications requiring
More informationCarrier frequency estimation. ELEC-E5410 Signal processing for communications
Carrier frequency estimation ELEC-E54 Signal processing for communications Contents. Basic system assumptions. Data-aided DA: Maximum-lielihood ML estimation of carrier frequency 3. Data-aided: Practical
More informationFlat Rayleigh fading. Assume a single tap model with G 0,m = G m. Assume G m is circ. symmetric Gaussian with E[ G m 2 ]=1.
Flat Rayleigh fading Assume a single tap model with G 0,m = G m. Assume G m is circ. symmetric Gaussian with E[ G m 2 ]=1. The magnitude is Rayleigh with f Gm ( g ) =2 g exp{ g 2 } ; g 0 f( g ) g R(G m
More informationFilter Design Problem
Filter Design Problem Design of frequency-selective filters usually starts with a specification of their frequency response function. Practical filters have passband and stopband ripples, while exhibiting
More informationDiscussion on FFE and DFE Coefficients Calculation in COM. Guo-HauGau, Mau-Lin Wu, Pei-Rong Li, Yuan-Hao Tung MediaTek IEEE 802.
Discussion on FFE and DFE Coefficients Calculation in COM Guo-HauGau, Mau-Lin Wu, Pei-Rong Li, Yuan-Hao Tung MediaTek IEEE 802.3ck Task Force Outline o COM and channels used in this analysis o Non-Monotonic
More informationThe basic structure of the L-channel QMF bank is shown below
-Channel QMF Bans The basic structure of the -channel QMF ban is shown below The expressions for the -transforms of various intermediate signals in the above structure are given by Copyright, S. K. Mitra
More informationSolutions to Selected Problems
Solutions to Selected Problems from Madhow: Fundamentals of Digital Communication and from Johannesson & Zigangirov: Fundamentals of Convolutional Coding Saif K. Mohammed Department of Electrical Engineering
More informationGaussian Random Variables Why we Care
Gaussian Random Variables Why we Care I Gaussian random variables play a critical role in modeling many random phenomena. I By central limit theorem, Gaussian random variables arise from the superposition
More informationIssues with sampling time and jitter in Annex 93A. Adam Healey IEEE P802.3bj Task Force May 2013
Issues with sampling time and jitter in Annex 93A Adam Healey IEEE P802.3bj Task Force May 2013 Part 1: Jitter (comment #157) 2 Treatment of jitter in COM Draft 2.0 h (0) (t s ) slope h(0) (t s ) 1 UI
More informationECE 564/645 - Digital Communications, Spring 2018 Homework #2 Due: March 19 (In Lecture)
ECE 564/645 - Digital Communications, Spring 018 Homework # Due: March 19 (In Lecture) 1. Consider a binary communication system over a 1-dimensional vector channel where message m 1 is sent by signaling
More informationInformation Theoretic Imaging
Information Theoretic Imaging WU Faculty: J. A. O Sullivan WU Doctoral Student: Naveen Singla Boeing Engineer: James Meany First Year Focus: Imaging for Data Storage Image Reconstruction Data Retrieval
More information112 Gbps In and Out of Package Challenges Design insights from electromagnetic analysis. Yuriy Shlepnev, Simberian Inc.
112 Gbps In and Out of Package Challenges Design insights from electromagnetic analysis Yuriy Shlepnev, Simberian Inc. shlepnev@simberian.com Package and PCB scales in symbol time for 112 Gbps PAM4 Package:
More informationElectromagnetic Wave Absorption Technology for Stub Effects Mitigation
TITLE Electromagnetic Wave Absorption Technology for Stub Effects Mitigation Image Shaowu Huang, Kai Xiao, Beomtaek Lee Intel Corporation January 20, 2016 Basic Physical Idea: Reduce the stub effects by
More informationApproximate Minimum Bit-Error Rate Multiuser Detection
Approximate Minimum Bit-Error Rate Multiuser Detection Chen-Chu Yeh, Renato R. opes, and John R. Barry School of Electrical and Computer Engineering Georgia Institute of Technology, Atlanta, Georgia 30332-0250
More informationKeysight Technologies Heidi Barnes
Keysight Technologies 2018.03.29 Heidi Barnes 1 S I G N A L I N T E G R I T Y A N D P O W E R I N T E G R I T Y Hewlett-Packard Agilent Technologies Keysight Technologies Bill and Dave s Company and the
More informationBlind Source Separation with a Time-Varying Mixing Matrix
Blind Source Separation with a Time-Varying Mixing Matrix Marcus R DeYoung and Brian L Evans Department of Electrical and Computer Engineering The University of Texas at Austin 1 University Station, Austin,
More informationMODULATION AND CODING FOR QUANTIZED CHANNELS. Xiaoying Shao and Harm S. Cronie
MODULATION AND CODING FOR QUANTIZED CHANNELS Xiaoying Shao and Harm S. Cronie x.shao@ewi.utwente.nl, h.s.cronie@ewi.utwente.nl University of Twente, Faculty of EEMCS, Signals and Systems Group P.O. box
More informationSIGNAL COMPRESSION. 8. Lossy image compression: Principle of embedding
SIGNAL COMPRESSION 8. Lossy image compression: Principle of embedding 8.1 Lossy compression 8.2 Embedded Zerotree Coder 161 8.1 Lossy compression - many degrees of freedom and many viewpoints The fundamental
More informationBandwidth of op amps. R 1 R 2 1 k! 250 k!
Bandwidth of op amps An experiment - connect a simple non-inverting op amp and measure the frequency response. From the ideal op amp model, we expect the amp to work at any frequency. Is that what happens?
More informationSolution for Problem 7.1. We argue by contradiction. If the limit were not infinite, then since τ M (ω) is nondecreasing we would have
362 Problem Hints and Solutions sup g n (ω, t) g(ω, t) sup g(ω, s) g(ω, t) µ n (ω). t T s,t: s t 1/n By the uniform continuity of t g(ω, t) on [, T], one has for each ω that µ n (ω) as n. Two applications
More informationDirect-Sequence Spread-Spectrum
Chapter 3 Direct-Sequence Spread-Spectrum In this chapter we consider direct-sequence spread-spectrum systems. Unlike frequency-hopping, a direct-sequence signal occupies the entire bandwidth continuously.
More informationSoft input/output LMS Equalizer
Soft input/output Equalizer Jacob H. Gunther 1 Todd K. Moon 1 Aleksey Orekhov 2 Dan Monroe 3 1 Utah State University 2 Cooper Union 3 Bradley University August 12, 29 Equalizer Block Diagram Equalizer
More informationDigital Communications: A Discrete-Time Approach M. Rice. Errata. Page xiii, first paragraph, bare witness should be bear witness
Digital Communications: A Discrete-Time Approach M. Rice Errata Foreword Page xiii, first paragraph, bare witness should be bear witness Page xxi, last paragraph, You know who you. should be You know who
More informationRandom Process Examples 1/23
ando Process Eaples /3 E. #: D-T White Noise Let ] be a sequence of V s where each V ] in the sequence is uncorrelated with all the others: E{ ] ] } 0 for This DEFINES a DT White Noise Also called Uncorrelated
More informationVID3: Sampling and Quantization
Video Transmission VID3: Sampling and Quantization By Prof. Gregory D. Durgin copyright 2009 all rights reserved Claude E. Shannon (1916-2001) Mathematician and Electrical Engineer Worked for Bell Labs
More informationCoherentDetectionof OFDM
Telematics Lab IITK p. 1/50 CoherentDetectionof OFDM Indo-UK Advanced Technology Centre Supported by DST-EPSRC K Vasudevan Associate Professor vasu@iitk.ac.in Telematics Lab Department of EE Indian Institute
More informationDigital Signal Processing
COMP ENG 4TL4: Digital Signal Processing Notes for Lecture #21 Friday, October 24, 2003 Types of causal FIR (generalized) linear-phase filters: Type I: Symmetric impulse response: with order M an even
More informationMassachusetts Institute of Technology Department of Electrical Engineering and Computer Science. Fall Solutions for Problem Set 2
Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science Issued: Tuesday, September 5. 6.: Discrete-Time Signal Processing Fall 5 Solutions for Problem Set Problem.
More informationPMD Compensator and PMD Emulator
by Yu Mimura *, Kazuhiro Ikeda *, Tatsuya Hatano *, Takeshi Takagi *, Sugio Wako * and Hiroshi Matsuura * As a technology for increasing the capacity to meet the growing demand ABSTRACT for communications
More informationIntegrated Circuits for Digital Communications
Integrated Circuits for Digital Communications Prof. David Johns (johns@eecg.toronto.edu) (www.eecg.toronto.edu/~johns) slide 1 of 72 Basic Baseband PAM Concepts slide 2 of 72 General Data Communication
More information26. Filtering. ECE 830, Spring 2014
26. Filtering ECE 830, Spring 2014 1 / 26 Wiener Filtering Wiener filtering is the application of LMMSE estimation to recovery of a signal in additive noise under wide sense sationarity assumptions. Problem
More informationDSP IC, Solutions. The pseudo-power entering into the adaptor is: 2 b 2 2 ) (a 2. Simple, but long and tedious simplification, yields p = 0.
5 FINITE WORD LENGTH EFFECTS 5.4 For a two-ort adator we have: b a + α(a a ) b a + α(a a ) α R R R + R The seudo-ower entering into the adator is: R (a b ) + R (a b ) Simle, but long and tedious simlification,
More informationencoding without prediction) (Server) Quantization: Initial Data 0, 1, 2, Quantized Data 0, 1, 2, 3, 4, 8, 16, 32, 64, 128, 256
General Models for Compression / Decompression -they apply to symbols data, text, and to image but not video 1. Simplest model (Lossless ( encoding without prediction) (server) Signal Encode Transmit (client)
More informationNSLMS: a Proportional Weight Algorithm for Sparse Adaptive Filters
NSLMS: a Proportional Weight Algorithm for Sparse Adaptive Filters R. K. Martin and C. R. Johnson, Jr. School of Electrical Engineering Cornell University Ithaca, NY 14853 {frodo,johnson}@ece.cornell.edu
More information3.9 Diversity Equalization Multiple Received Signals and the RAKE Infinite-length MMSE Equalization Structures
Contents 3 Equalization 57 3. Intersymbol Interference and Receivers for Successive Message ransmission........ 59 3.. ransmission of Successive Messages.......................... 59 3.. Bandlimited Channels..................................
More informationFree-Space MEMS Tunable Optical Filter in (110) Silicon
Free-Space MEMS Tunable Optical Filter in (110) Silicon Ariel Lipson & Eric M. Yeatman Optical & Semiconductor Group Outline Device - Optical Filter Optical analysis Fabrication Schematic Fabricated 2
More informationOptimal Design of Real and Complex Minimum Phase Digital FIR Filters
Optimal Design of Real and Complex Minimum Phase Digital FIR Filters Niranjan Damera-Venkata and Brian L. Evans Embedded Signal Processing Laboratory Dept. of Electrical and Computer Engineering The University
More informationthat efficiently utilizes the total available channel bandwidth W.
Signal Design for Band-Limited Channels Wireless Information Transmission System Lab. Institute of Communications Engineering g National Sun Yat-sen University Introduction We consider the problem of signal
More informationCourse and Wavelets and Filter Banks. Filter Banks (contd.): perfect reconstruction; halfband filters and possible factorizations.
Course 18.327 and 1.130 Wavelets and Filter Banks Filter Banks (contd.): perfect reconstruction; halfband filters and possible factorizations. Product Filter Example: Product filter of degree 6 P 0 (z)
More informationSignal Design for Band-Limited Channels
Wireless Information Transmission System Lab. Signal Design for Band-Limited Channels Institute of Communications Engineering National Sun Yat-sen University Introduction We consider the problem of signal
More informationModeling I/O Links With X Parameters
Modeling I/O Links With X Parameters José E. Schutt Ainé and Pavle Milosevic Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign Urbana, IL 61801 Wendemagegnehu
More information10GBASE-T PCS details and Precoding
10GBASE-T PCS details and Precoding with additions of 24Jan05 IEEE P802.3an Task Force Vancouver, January 26-28, 2005 Gottfried Ungerboeck 1 IEEE P802.3an Nov 2004 Plenary CRC and Scrambling - in which
More informationUTA EE5362 PhD Diagnosis Exam (Spring 2011)
EE5362 Spring 2 PhD Diagnosis Exam ID: UTA EE5362 PhD Diagnosis Exam (Spring 2) Instructions: Verify that your exam contains pages (including the cover shee. Some space is provided for you to show your
More informationIntroduction to Constrained Estimation
Introduction to Constrained Estimation Graham C. Goodwin September 2004 2.1 Background Constraints are also often present in estimation problems. A classical example of a constrained estimation problem
More informationMaximum-Likelihood fitting
CMP 0b Lecture F. Sigworth Maximum-Likelihood fitting One of the issues I want to address in this lecture is the fitting of distributions dwell times. We want to find the best curve to draw over a histogram,
More informationOn VDSL Performance and Hardware Implications for Single Carrier Modulation Transceivers
On VDSL Performance and ardware Implications for Single Carrier Modulation Transceivers S. AAR, R.ZUKUNFT, T.MAGESACER Institute for Integrated Circuits - BRIDGELAB Munich University of Technology Arcisstr.
More informationApplication of Principal Component Analysis to TES data
Application of Principal Component Analysis to TES data Clive D Rodgers Clarendon Laboratory University of Oxford Madison, Wisconsin, 27th April 2006 1 My take on the PCA business 2/41 What is the best
More informationFiber Modeling Resolution and Assumptions: Analysis, Data, and Recommendations
Fiber Modeling Resolution and Assumptions: Analysis, Data, and Recommendations GaTech: Kasyapa Balemarthy, Stephen Ralph OFS: Robert Lingle, Jr., George Oulundsen, Yi Sun, John George Corning: John Abbott
More informationShallow Water Fluctuations and Communications
Shallow Water Fluctuations and Communications H.C. Song Marine Physical Laboratory Scripps Institution of oceanography La Jolla, CA 92093-0238 phone: (858) 534-0954 fax: (858) 534-7641 email: hcsong@mpl.ucsd.edu
More informationBASICS OF DETECTION AND ESTIMATION THEORY
BASICS OF DETECTION AND ESTIMATION THEORY 83050E/158 In this chapter we discuss how the transmitted symbols are detected optimally from a noisy received signal (observation). Based on these results, optimal
More informationEE4304 C-term 2007: Lecture 17 Supplemental Slides
EE434 C-term 27: Lecture 17 Supplemental Slides D. Richard Brown III Worcester Polytechnic Institute, Department of Electrical and Computer Engineering February 5, 27 Geometric Representation: Optimal
More informationBlind phase/frequency synchronization with low-precision ADC: a Bayesian approach
Blind phase/frequency synchronization with low-precision ADC: a Bayesian approach Aseem Wadhwa, Upamanyu Madhow Department of ECE, UCSB 1/26 Modern Communication Receiver Architecture Analog Digital TX
More informationOptimized Impulses for Multicarrier Offset-QAM
Optimized Impulses for ulticarrier Offset-QA Stephan Pfletschinger, Joachim Speidel Institut für Nachrichtenübertragung Universität Stuttgart, Pfaffenwaldring 47, D-7469 Stuttgart, Germany Abstract The
More informationEffect of Nonlinearity on PMD Compensation in a Single-Channel 10-Gb/s NRZ System
The Open Optics Journal, 28, 2, 53-6 53 Open Access Effect of Nonlinearity on PMD Compensation in a Single-Channel -Gb/s NRZ System John Cameron *,,2, Xiaoyi Bao and Liang Chen Physics Department, University
More informationLinear Optimum Filtering: Statement
Ch2: Wiener Filters Optimal filters for stationary stochastic models are reviewed and derived in this presentation. Contents: Linear optimal filtering Principle of orthogonality Minimum mean squared error
More informationCHROMATIC DISPERSION COMPENSATION USING COMPLEX-VALUED ALL-PASS FILTER. Jawad Munir, Amine Mezghani, Israa Slim and Josef A.
CHROMAIC DISPERSION COMPENSAION USING COMPLEX-VALUED ALL-PASS FILER Jawad Munir, Amine Mezghani, Israa Slim and Josef A. Nossek Institute for Circuit heory and Signal Processing, echnische Universität
More information