BLIND CROSSTALK CANCELLATION FOR DMT SYSTEMS

Slides:



Advertisements
Similar presentations
Feedback Reliability Calculation for an Iterative Block Decision Feedback Equalizer (IB-DFE) Gillian Huang, Andrew Nix and Simon Armour Centre for Communications.
Advertisements

(Orthogonal Frequency Division Multiplexing )
Digital Subscriber Line (DSL)
Multiuser Detection for CDMA Systems
ECE 8443 – Pattern Recognition ECE 8423 – Adaptive Signal Processing Objectives: The Linear Prediction Model The Autocorrelation Method Levinson and Durbin.
1 xDSL Technical Overview Oct DSL Market Drivers & Enablers Service Provider Drivers  Telco's desire to compete with Cable companies  Additional.
1 Helsinki University of Technology,Communications Laboratory, Timo O. Korhonen Data Communication, Lecture6 Digital Baseband Transmission.
Authors: David N.C. Tse, Ofer Zeitouni. Presented By Sai C. Chadalapaka.
Broadband local access technology
1 Broadband Access technologies As the multimedia content grows, we need faster internet connectivity for SOHO users. Broadband access technologies shown.
ECE 8443 – Pattern Recognition ECE 8423 – Adaptive Signal Processing Objectives: The FIR Adaptive Filter The LMS Adaptive Filter Stability and Convergence.
ISWCS’06, Valencia, Spain 1 Blind Adaptive Channel Shortening by Unconstrained Optimization for Simplified UWB Receiver Design Authors: Syed Imtiaz Husain.
Multiuser Detection in CDMA A. Chockalingam Assistant Professor Indian Institute of Science, Bangalore-12
Ethernet over VDSL Technical Specifications. Agenda –Rate – Reach –Band Allocation –SNR and BER –PSD mask and Power Backoff Algorithm –Rate Limitation.
IERG 4100 Wireless Communications
1 Audio Compression Techniques MUMT 611, January 2005 Assignment 2 Paul Kolesnik.
WAN Technologies Lecture 9 Paul Flynn.
EE360: Lecture 8 Outline Multiuser Detection
Module 2.2: ADSL, ISDN, SONET
Digital to analogue conversion. 1 DIGITAL-TO-ANALOG CONVERSION Digital-to-analog conversion is the process of changing one of the characteristics (A,
Dept. of EE, NDHU 1 Chapter Three Baseband Demodulation/Detection.
Formatting and Baseband Modulation
Modulation, Demodulation and Coding Course
Lecture 1. References In no particular order Modern Digital and Analog Communication Systems, B. P. Lathi, 3 rd edition, 1998 Communication Systems Engineering,
Digital Communication I: Modulation and Coding Course
Rake Reception in UWB Systems Aditya Kawatra 2004EE10313.
GSC /09/2015GSC-8, OTTAWA Rick Townsend T1E1 Chairman Wayne Zeuch T1 Vice Chairman Status Report of Digital Subscriber Line Work in Committee T1.
Software Defined Radio
Blind Beamforming for Cyclostationary Signals
Multiuser Detection (MUD) Combined with array signal processing in current wireless communication environments Wed. 박사 3학기 구 정 회.
ECE 4331, Fall, 2009 Zhu Han Department of Electrical and Computer Engineering Class 16 Oct. 20 th, 2007.
Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen {moonen, vanbleu,
DSP2 Project ADSL Equalization Students: Dung Nguyen Quoc- Master Student Tudor Tesu- Erasmus Student Supervisor Jan Vangorp.
VADA Lab.SungKyunKwan Univ. 1 L40: Lower Power Equalizer J. W. Kim and J.D.Cho 성균관대학교
The Physical Layer Lowest layer in Network Hierarchy. Physical transmission of data. –Various flavors Copper wire, fiber optic, etc... –Physical limits.
Space-Time and Space-Frequency Coded Orthogonal Frequency Division Multiplexing Transmitter Diversity Techniques King F. Lee.
Motivation Wireless Communication Environment Noise Multipath (ISI!) Demands Multimedia applications  High rate Data communication  Reliability.
EE 3220: Digital Communication
Decision Feedback Equalization in OFDM with Long Delay Spreads
A Semi-Blind Technique for MIMO Channel Matrix Estimation Aditya Jagannatham and Bhaskar D. Rao The proposed algorithm performs well compared to its training.
Digital Communications Chapeter 3. Baseband Demodulation/Detection Signal Processing Lab.
Jump to first page New algorithmic approach for estimating the frequency and phase offset of a QAM carrier in AWGN conditions Using HOC.
Dept. of EE, NDHU 1 Chapter One Signals and Spectra.
Spectrum Sensing In Cognitive Radio Networks
Baseband Receiver Receiver Design: Demodulation Matched Filter Correlator Receiver Detection Max. Likelihood Detector Probability of Error.
COMPUTER NETWORKING 2 LECTURE 3: BROADBAND TECHNOLOGY & DSL.
Single Correlator Based UWB Receiver Implementation through Channel Shortening Equalizer By Syed Imtiaz Husain and Jinho Choi School of Electrical Engineering.
Performance of Digital Communications System
Chapter 9 Using Telephone and Cable Networks for Data Transmission.
Chapter 9 Using Telephone and Cable Networks for Data Transmission.
Space-Time and Space-Frequency Coded Orthogonal Frequency Division Multiplexing Transmitter Diversity Techniques King F. Lee.
Power Line Communications for Enabling Smart Grid Applications
Asymmetric Digital Subscriber Line
Yousof Mortazavi, Aditya Chopra, and Prof. Brian L. Evans
J. W. Kim and J.D.Cho 성균관대학교 Lower Power Equalizer J. W. Kim and J.D.Cho 성균관대학교 SungKyunKwan Univ.
Equalization in a wideband TDMA system
Waveform Generation for Waveform Coding
William Stallings Data and Computer Communications
Digital Subscriber Line Technology
Implementation Platform
ELEG 6203: "Wireles Networks" Wireless Networks December 04,2003
Powerline Communications: Channel Characterization and Modem Design
Chapter 9. High-Speed Digital Access: DSL, Cable Modems
PCM & DPCM & DM.
Digital Subscriber Line Technology
On the Design of RAKE Receivers with Non-uniform Tap Spacing
Spectral line suppression for MC-OOK
Govt. Polytechnic Dhangar(Fatehabad)
EXPLOITING SYMMETRY IN TIME-DOMAIN EQUALIZERS
Digital Subscriber Line Technology
Presentation transcript:

BLIND CROSSTALK CANCELLATION FOR DMT SYSTEMS Nadeem Ahmed Nirmal Warke ECE Dept. DSPS R&D Center Rice University Texas Instruments

Motivation New multimedia and networking applications => increasing demand for bandwidth DSL is cost effective broadband solution 100 MHz 10 MHz 1 MHz 100 kHz 10 kHz POTS ADSL VDSL ISDN HDSL

Motivation Increasing density of DSL deployment => Increased crosstalk Crosstalk typically increases with frequency => significant impairment for high speed DSL Binder ADSL lines HDSL lines POTS

Types of Crosstalk Near-End Crosstalk (NEXT): Interference that arises when signals are transmitted in opposite directions Far-End Crosstalk (FEXT): Interference that arises when signals are transmitted in the same direction

DSL System Model FEXT signals travel the entire length of the channel FDD modems virtually eliminate self-NEXT. Main source of crosstalk comes from other services (i.e. HDSL, T1, etc), which are much stronger than self-FEXT.

Crosstalk Power on Line

Combating Crosstalk Crosstalk Avoidance Crosstalk Cancellation Varying transmit spectra Modified bit-loading algorithm Block coding across modems at CO Crosstalk Cancellation Treat as multiuser detection problem Using DFE’s Exploit symbol rate differences

Varying Transmit Spectra Design optimal transmit spectra which vary with channel, noise and interference Designed to reject self-NEXT in a manner which maximizes overall data rate Maintains spectral compatibility with other services

Modified Bit-Loading Algorithm Modify the bit-loading algorithm Change order of placing power in bins Factor NEXT into algorithm Minimizes NEXT within cable binder and extend reach of service

Block Coding Across COs Block coding to eliminate NEXT If code blocks are greater than a minimum length, NEXT can be completely eliminated Need control of a service i.e., all DSL modems only useful for self-NEXT rejection

Multi-User Detection Use multiuser detection techniques to cancel crosstalk Jointly detect desired and crosstalk signals Published results for Home LAN interference cancellation from VDSL

DFE For Self-NEXT/FEXT Use DFE to remove cyclo-stationary crosstalk Assumes crosstalk has same sampling rate as source Useful for self-NEXT and self-FEXT cancellation

Excess Band Crosstalk Cancellation Crosstalkers like ISDN, HDSL, T1 have large excess band Algorithm Exploits lower symbol rate of crosstalker relative to the sampling rate of DSL Crosstalker estimated in excess band and cancelled in main band

Practical Issues Most methods require knowledge of crosstalk coupling function How do you reliably estimate the coupling function- Use models? Based on training data? Very difficult problem

Excess Band Crosstalk Cancellation Paper by Zeng et al on Crosstalk Cancellation for DMT Systems

Excess Band Crosstalk Cancellation Brick wall filters cannot be realized After D/A conversion, filter cannot remove all of image energy If crosstalk signal is oversampled with respect to xDSL, excess band can be observed Estimate crosstalk signal in excess band and predict crosstalk in main band

Mathematical Formulation DMT Modulation System Impaiments- crosstalk and noise DMT Demodulation

Mathematical Formulation Partition into 2 freq. Bands: 2 => main band 1 => excess band Demodulate DMT signal in excess band and subtract to estimate crosstalk signal

Cancellation Algorithm Let x = M.r be a linear estimate of crosstalk signal component x MMSE Estimate: Hence crosstalk signal in main band is, Project onto main band M

Blind Cancellation If = .C and x = b, channel is assumed to be known => Zeng’s solution Instead, let = and x = C.b => Blind Approach Solution uses crosstalk statistics i.e. autocorrelation information Estimate coupling function and crosstalk data simultaneously

Dependence on crosstalk symbol delay Relative crosstalk symbol delay varies with DMT frame => varies with DMT frame where,

Blind Cancellation- Practical Solution Autocorrelation can be easily estimated during training and/or quiet periods Crosstalk cancellation matrix can be pre-computed and stored Steady state operation involves product of cancellation matrix with vector r Practical to implement

Crosstalk Simulations Consider an ADSL system: Transmission bandwidth: (25.875, 1104) kHz 256 tones over 1104 kHz bandwidth AWGN at –140 dBm/Hz Crosstalk: 1 HDSL (f_N=192kHz) and 1 T1 (f_N=772kHz) Assumption Assume crosstalk symbol delay is known to within some finite precision

Crosstalk Measurements Used vector signal analyzer 12 wire twisted pair cable binder (4000 ft) Used periodic chirp as input signal Captured magnitude and phase of transfer function

Channel Measurements 4000 ft, 24AWG, 21 pair wire binder

NEXT Coupling Functions From 1 into 2 From 11 into 5 4000 ft, 24AWG, 21 pair wire binder

HDSL Crosstalk Cancellation 15/12dB average crosstalk energy reduction for Q(T/4)/Q(T/2)

HDSL Crosstalk Cancellation 1500/1000ft average reach improvement at 1Mbps for Q(T/4)/Q(T/2)

HDSL+T1 Crosstalk Cancellation require 2x oversampled receiver 12/7dB average crosstalk energy reduction for Q(T/4)/Q(T/2)

HDSL+T1 Crosstalk Cancellation 2000/1500ft average reach improvement at 1Mbps for Q(T/4)/Q(T/2)

Conclusions Blind crosstalk cancellation method uses statistical properties of received signal Signal cancellation matrix can be pre-computed (steady state operation involves inner products) Simulations show significant gain for realistic ADSL system Performance is robust to jitter in crosstalk symbol timing estimate

Future Work Investigate methods for estimating crosstalk symbol timing Study effect of incorrect DMT decisions in excess band on cancellation performance (multiple crosstalkers) Investigate alternative crosstalk cancellation methods