ADAPTIVE EQUALIZATION AT MULTI-GHZ DATARATES

Similar documents
Similarities of PMD and DMD for 10Gbps Equalization

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

Weiyao Lin. Shanghai Jiao Tong University. Chapter 5: Digital Transmission through Baseband slchannels Textbook: Ch

Square Root Raised Cosine Filter

14 Gb/s AC Coupled Receiver in 90 nm CMOS. Masum Hossain & Tony Chan Carusone University of Toronto

ECEN689: Special Topics in High-Speed Links Circuits and Systems Spring 2012

EE4601 Communication Systems

EE4061 Communication Systems

EE5713 : Advanced Digital Communications

Adaptive Polarization Mode Dispersion Compensation at 40Gb/s with Integrated Optical Finite Impulse Response (FIR) Filters

Leistungsfähigkeit von elektronischen Entzerrer in hochbitratigen optischen Übertragungsystemen. S. Otte, W. Rosenkranz. chair for communications,

Revision of Lecture 4

Digital Baseband Systems. Reference: Digital Communications John G. Proakis

Analog Electronics 2 ICS905

CMOS Cross Section. EECS240 Spring Today s Lecture. Dimensions. CMOS Process. Devices. Lecture 2: CMOS Technology and Passive Devices

RADIO SYSTEMS ETIN15. Lecture no: Equalization. Ove Edfors, Department of Electrical and Information Technology

IEEE 802.3ap Task Force Ottawa Sept 27-29, 2004

Motivation for CDR: Deserializer (1)

Signal Design for Band-Limited Channels

LECTURE 16 AND 17. Digital signaling on frequency selective fading channels. Notes Prepared by: Abhishek Sood

Polarization division multiplexing system quality in the presence of polarization effects

ELECTRONIC EQUALIZATION OF HIGH-SPEED MULTI-MODE FIBER LINKS

that efficiently utilizes the total available channel bandwidth W.

Propagation losses in optical fibers

Preliminary Studies on DFE Error Propagation, Precoding, and their Impact on KP4 FEC Performance for PAM4 Signaling Systems

CMOS Cross Section. EECS240 Spring Dimensions. Today s Lecture. Why Talk About Passives? EE240 Process

Principles of Communications

SerDes_Channel_Impulse_Modeling_with_Rambus

II - Baseband pulse transmission

Projects in Wireless Communication Lecture 1

EE290C Spring Motivation. Lecture 6: Link Performance Analysis. Elad Alon Dept. of EECS. Does eqn. above predict everything? EE290C Lecture 5 2

Asymptotic Capacity Bounds for Magnetic Recording. Raman Venkataramani Seagate Technology (Joint work with Dieter Arnold)

Decision-Point Signal to Noise Ratio (SNR)

Nonlinearity Equalization Techniques for DML- Transmission Impairments

Direct-Sequence Spread-Spectrum

PMD Compensator and PMD Emulator

Optical Component Characterization: A Linear Systems Approach

Pulse Shaping and ISI (Proakis: chapter 10.1, 10.3) EEE3012 Spring 2018

FBMC/OQAM transceivers for 5G mobile communication systems. François Rottenberg

EECS240 Spring Today s Lecture. Lecture 2: CMOS Technology and Passive Devices. Lingkai Kong EECS. EE240 CMOS Technology

OPTICAL COMMUNICATIONS S

THE IMPACT POLARIZATION MODE DISPERSION OPTICAL DUOBINARY TRANSMISSION

Imperfect Sampling Moments and Average SINR

Chapter 10. Timing Recovery. March 12, 2008

Information Theory for Dispersion-Free Fiber Channels with Distributed Amplification

Preamplifier in 0.5µm CMOS

Lecture 2. Fading Channel

8.1 Circuit Parameters

A Family of Nyquist Filters Based on Generalized Raised-Cosine Spectra

ELEC E7210: Communication Theory. Lecture 4: Equalization

Electronic Circuits Summary

Optical Fiber Signal Degradation

Non-Sinusoidal Waves on (Mostly Lossless)Transmission Lines

Optimal Placement of Training Symbols for Frequency Acquisition: A Cramér-Rao Bound Approach

ELEN E4810: Digital Signal Processing Topic 11: Continuous Signals. 1. Sampling and Reconstruction 2. Quantization

Line Codes and Pulse Shaping Review. Intersymbol interference (ISI) Pulse shaping to reduce ISI Embracing ISI

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

Revision of Lecture 4

Computation of Bit-Error Rate of Coherent and Non-Coherent Detection M-Ary PSK With Gray Code in BFWA Systems

Performance Analysis of Spread Spectrum CDMA systems

Lecture 7: Wireless Channels and Diversity Advanced Digital Communications (EQ2410) 1

ARCC Workshop on Time-reversal communications in richly scattering environments. Large-Delay-Spread Channels: Mathematical models and fast algorithms

UNIT 1. SIGNALS AND SYSTEM

Timing Recovery at Low SNR Cramer-Rao bound, and outperforming the PLL

Optoelectronic Applications. Injection Locked Oscillators. Injection Locked Oscillators. Q 2, ω 2. Q 1, ω 1

Example: Bipolar NRZ (non-return-to-zero) signaling

Blind phase/frequency synchronization with low-precision ADC: a Bayesian approach

ANALYSIS OF A PARTIAL DECORRELATOR IN A MULTI-CELL DS/CDMA SYSTEM

Optical solitons and its applications

Estimation of the Capacity of Multipath Infrared Channels

ADAPTIVE FILTER ALGORITHMS. Prepared by Deepa.T, Asst.Prof. /TCE

Channel Estimation with Low-Precision Analog-to-Digital Conversion

CS6956: Wireless and Mobile Networks Lecture Notes: 2/4/2015

Digital Communications

Data Detection for Controlled ISI. h(nt) = 1 for n=0,1 and zero otherwise.

High Speed Communication Circuits and Systems Lecture 4 Generalized Reflection Coefficient, Smith Chart, Integrated Passive Components

Advantages of Using CMOS

Broadband material model identification with GMS-parameters

Effect of Nonlinearity on PMD Compensation in a Single-Channel 10-Gb/s NRZ System

Feedback Transimpedance & Current Amplifiers

Summary: ISI. No ISI condition in time. II Nyquist theorem. Ideal low pass filter. Raised cosine filters. TX filters

Lecture 15: Thu Feb 28, 2019

Data-aided and blind synchronization

Mobile Communications (KECE425) Lecture Note Prof. Young-Chai Ko

Efficient Semi-Blind Channel Estimation and Equalization Based on a Parametric Channel Representation

Single-Carrier Block Transmission With Frequency-Domain Equalisation

This examination consists of 11 pages. Please check that you have a complete copy. Time: 2.5 hrs INSTRUCTIONS

Raman Amplification for Telecom Optical Networks. Dominique Bayart Alcatel Lucent Bell Labs France, Research Center of Villarceaux

On VDSL Performance and Hardware Implications for Single Carrier Modulation Transceivers

Self-Phase Modulation in Optical Fiber Communications: Good or Bad?

EE4512 Analog and Digital Communications Chapter 4. Chapter 4 Receiver Design

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

Communication Theory Summary of Important Definitions and Results

Electronic Circuits. Prof. Dr. Qiuting Huang Integrated Systems Laboratory

RFIC2017 MO2B-2. A Simplified CMOS FET Model using Surface Potential Equations For Inter-modulation Simulations of Passive-Mixer-Like Circuits

LOPE3202: Communication Systems 10/18/2017 2

Approximate Best Linear Unbiased Channel Estimation for Frequency Selective Channels with Long Delay Spreads: Robustness to Timing and Carrier Offsets

Lecture 3 Fiber Optical Communication Lecture 3, Slide 1

Lecture 9. PMTs and Laser Noise. Lecture 9. Photon Counting. Photomultiplier Tubes (PMTs) Laser Phase Noise. Relative Intensity

Lecture 4 Fiber Optical Communication Lecture 4, Slide 1

Transcription:

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 & Digital FIR Filter. - Analog Traveling Wave and Transversal Equalizers. Problems and prospects of analog adaptive filters. Conclusions

Non-Return-to-Zero (NRZ) Data Transmission 0 1 0 0 1 bit period NRZ Pulse At 10 Gbps, 1 Bit period is 100 picoseconds

What is Inter-Symbol-Interference? Tx 0 1 0 0 0 1 0 1 Ch 1 Ch 2

Why is ISI Bad? 0 1 0 1 Smaller "Distance" Smaller separation, more likely to make an error

What is an Eye Diagram? Graphics Source : Electronic Design Magazine

Eye Diagram : No ISI, no noise 1.1 0.91 0.76 Amplitude 0.61 0.46 0.3 0.15 0 0 25 50 75 100 125 150 175 200 Time (ps)

Eye Diagram : No ISI, with noise 1.4 1.2 0.94 Amplitude 0.71 0.47 0.24 0 0.24 0 25 50 75 100 125 150 175 200 Time (ps)

Eye Diagram : With ISI, no noise 1.1 0.91 0.76 Amplitude 0.61 0.45 0.3 0.15 0 0 25 50 75 100 125 150 175 200 Time (ps)

Eye Diagram : With ISI, with noise 1.3 1.1 0.89 Amplitude 0.67 0.45 0.22 0 0.22 0 25 50 75 100 125 150 175 200 Time (ps)

Typical Optical Fiber Data Link Photodiode Receiver Transmitter Fiber

Typical Optical Fiber Data Link Photodiode Receiver Transmitter Fiber TIA Transimpedance Amplifier LA Limiting Amplifier CDR Clock/Data Recovery Data

Typical Optical Fiber Data Link Transimpedance Amplifier TIA Limiting Amplifier LA Clock/Data Recovery CDR Data

ISI in Optical Links Dispersion in fiber due to manufacturing tolerances Polarization Mode Dispersion in Single Mode Fiber Impulse Response : αδ(t) + (1 α)δ(t T d ) α is called the Power Split T d is called the Differential Group Delay (DGD) Two paths with different delays and gains Much worse (many more paths, greater spread) in multi-mode fibers

Example Eye : No ISI, Finite Tx Bandwidth 1.1 0.91 0.76 Amplitude 0.61 0.46 0.3 0.15 0 0 25 50 75 100 125 150 175 200 Time (ps)

PMD, Finite Tx BW, DGD = 75 ps 1.1 0.91 0.76 Amplitude 0.6 0.45 0.3 0.15 0 0 25 50 75 100 125 150 175 200 Time (ps)

PMD, Finite Tx BW, DGD = 75 ps & Noise 1.2 1 0.82 0.62 0.41 0.21 0 0.21 0 25 50 75 100 125 150 175 200

Mitigating ISI Input Channel Output 1 β y(t) y(t) - βy(t-t b ) + β 2 y(t-2t b ) 1 1 β y(t) y(t-t b ) β 1 β 1 y(t-2t b ) y(t) β βy(t-t b ) β β 2 + β 2 y(t-2t b ) β 2 β 3 1 β 3

Mitigating ISI : Equalization 1/T b Input Channel Output T b T b T b w 1 w 2 w 3 w 4 Output(nT b ) = k=n 1 k=0 Σ Output w k y(nt b kt b ) (1) Tapped-delay line Equalizer Weights need to be adaptive, since channel is varying (slowly) with time

Mitigating ISI : Equalization 1/T b Channel Filter T Input b T b T b w 1 w 2 w 3 w 4 Σ Output 4 tap" adaptive equalizer Need a filter before sampling Called the matched filter"

Digital Receiver : Baud Spaced Equalizer (BSE) TIA/VGA FILTER ADC 10 Gbps 6-bit Timing Phase sensitivity in a BSE High speed (10 Gbps), 6-bit ADC Digital FIR LMS ENGINE Data Example : Bell Labs (2003) - 6-bit 10 G ADC - 3.5 W and yields 4 effective bits in 0.18µm SiGe BiCMOS Technology (state of the art) Parallelism in the equalizer - more area

Digital Receiver : Baud Spaced Equalizer (BSE) 10 Gbps 6-bit Digital FIR ADC Data FILTER TIA/VGA LMS ENGINE Too much power / area ADC is a big project in itself

Digital Receiver : Fractionally Spaced Equalizer (FSE) 20 Gbps 6-bit Digital FIR ADC Data FILTER TIA/VGA LMS ENGINE Insensitive to timing phase High speed (20 Gbps), 6-bit ADC! Parallelism in the equalizer

Digital Implementation : Summary Power hungry! ADC may be doable 10Gbps Solution doesnt scale well to higher speeds (40 Gbps)

Analog Implementation Analog Input Channel Filter T b T b T b w 1 w 2 w 3 w 4 Σ 1/T b Output Sampling after equalization Delays implemented using transmission lines FSE 10Gbps : Each delay line is 50 ps long

System Model b n ε { 0, 1} Σ b n δ(t - nt) IID BIT SOURCE Tx FILTER αδ(t) + (1-α)δ(t-τ) PMD CHANNEL FIBER LOSS (β) 1/β 4th Order Butterworth + TIA & VGA + EQUALIZER AA FILTER f s OUT Offset Correct AWGN

System Model a n ε { 1/2, 1/2} Σ a n δ(t - nt) αδ(t) + (1-α)δ(t-τ) 4th Order Butterworth IID BIT SOURCE Tx FILTER PMD CHANNEL + EQUALIZER AA FILTER f s OUT AWGN (b) w 1 x 1 (t) IID BIT SOURCE a n ε { 1/2, 1/2} Σa n δ(t - nt) p(t) Tx Filter & Channel + n(t) x 2 (t) w 2 AA Filter v ncir v i v r(t) out w N-1 y(t) x (N-1) (t) x N (t) w N f s y(n) OUT EQUALIZER (c)

System Model a n ε { 1/2, 1/2} Σa n δ(t - nt) x 1 (t) w 1 IID BIT SOURCE p(t) Tx Filter & Channel + n(t) v i x N (t) f s v out y(t) y(n) OUT w N EQUALIZER

MMSE solution a n ε { 1/2, 1/2} Σa n δ(t - nt) IID BIT SOURCE p(t) Tx Filter & Channel + n(t) v i x 1 (t) x N (t) w 1 f s vout y(t) y(n) OUT w N EQUALIZER c i (t) = p(t) x i (t) N y(t) = w i a(k) c i (t kt ) + i=1 k= N w i n(t) x i (t) N n N y(n) = w i a(k) c i (nt kt ) + w i (n(t) x i (t)) t=nt i=1 i=1 k= i=1

MMSE solution y(n) = N n i=1 k= w i a(k) c i (nt kt ) + N w i (n(t) x i (t)) t=nt i=1 c 1 (0.T ) c 2 (0.T )... c N (0.T ) y(n) = a T c 1 (T ) c 2 (T )... c N (T ) (n)...... c 1 (L.T ) c 2 (L.T )... c N (L.T ) w 1 w 2. w N +ηt (n) w 1 w 2. w N a T (n) = [a(n) a(n 1) a(n L)] η T (n) = [ (n(t) x 1 (t)) t=nt (n(t) x 2 (t)) t=nt (n(t) x N (t)) t=nt ] Equalizer output is y(n) = a T (n)cw + η T (n)w

MMSE solution Equalizer output & desired outputs are y(n) = a T (n)cw + η T (n)w y d (n) = a(n δ) = a T (n) h δ The error at the output of the equalizer is e(n) = y(n) a T (n)h δ = a T (n) (Cw h δ ) + η T (n)w [ e(n) 2] [ ] = (Cw h δ ) T E a(n) T a(n) (CW h δ )+w T E E [ a(n) T a(n) ] = σ 2 a I, where σ 2 a = E[ a(n) 2 ]. [ ] η T (n)η(n) w

MMSE solution E [ ] η T (n)η(n) = M = N o 2 0 x 1(t)x 1 (t)dt... 0 x 1(t)x N (t)dt 0 x 2(t)x 1 (t)dt... 0 x 2(t)x N (t)dt..... 0 x N(t)x 1 (t)dt... x N(t)x N (t)dt so that [ E e(n) 2] = σa 2 (Cw h δ ) T (Cw h δ ) + w T Mw 0 It can be shown that w opt = A 1 C T h δ MMSE = σa 2 h T δ (I CA 1 C T )h δ where A = C T C + M/σa 2

Tapped Delay Line Filters : Transversal G R T R T Z o, T Z o, T v i v 1 v 2 v 3 w 1 w 2 w 3 v g i v out R T /2 i = gv Delay Elements are passive Tap weights : variable gain amplifiers (Differential pair) Summation : Kirchoffs Current Law

Choices for On-chip Delay Lines : Microstrip Wideband Need 50 ps delay Velocity of light 150 µm/ps 50 ps 7.5 mm! (and we need several of them) Conclusion : No good What can we do to make the delay line smaller?

Spiral Delay Lines Metal 1 Metal 5 Spiral : reduces size Use metal interconnect layers Mutual coupling results in increased inductance

Spiral Delay Lines Metal 1 Metal 5 Ground plane is broken to avoid image currents Attempt to distribute capacitance uniformly across the inductor Typical size - 300µm on a side Accurate model through EM Simulations

Tunable Weights om op Vdd Sign S Q5,6 S Q7,8 S Vdd ip Q1 Q4 im Q2 Q3 Magnitude Example of a tunable tap weight implementation

Problems with Transversal Filters G R T Z o, T Z o, T R T v i v 1 v+ v+(t-2t) 1 >> Γ Τ >> Γ 2 Τ... h v1 (t) 1 Γ T v+(t-4t) Γ T v+(t-2t) Exponential tails due to series losses Components due to reflection Γ T 0 1 2 3 4 5 6 7 8 Equalizer Span t/t Mistermination & Loss in the delay lines Tap responses have components outside equalizer span ISI" within the equalizer! Degrades performance

Problems with Transversal Filters 1.1 0.95 Normalized Filter Output 0.79 0.63 0.47 0.32 0.16 0 0 25 50 75 100 125 150 175 200 time (ps) Eye diagram at the first tap output

Traveling Wave Amplifier (TWA) FIR Filter G R T Z o, T/2 Z o, T/2 R T v i v 1 v 2 v 3 w 1 w 2 w 3 Z o, T/2 Z o, T/2 v g i v out R T R T i = gv

Traveling Wave Amplifier (TWA) FIR Filter v i G R T Z o, T/2 Z o, T/2 R T v 1 v 2 v 3 h v1 (t) k 1 Γ T k=gz o (1+Γ Τ )/2 0 1 2 3 4 t/t v out w 1 w 2 w 3 Z o, T/2 Z o, T/2 h w1 (t) 1 k1 k1=k 2 /G 2Γ T 0 1 2 3 4 t/t R T R T

TWA FIR Filters : Comments Improvement over a transversal filter Robust with mistermination and series loss Used in several commerical equalizer ICs Two doubly terminated lines - Tap weights need to be larger by a factor of 2

Traveling Wave versus Transversal Equalizers NRZ response (V) 0.3 Tap 1 (a) Tap 10 0.2 0.1 0 2 4 6 8 10 12 14 16 t / T b NRZ response (V) 0.3 0.2 0.1 0 Tap 1 Tap 10 (b) 2 4 6 8 10 12 14 16 t / T b

Traveling Wave versus Transversal Equalizers Equalizer Output Receiver Input 1.3 1 0.84 0.63 0.42 0.21 0 0.21 1.6 1.3 0.99 0.66 0.33 1.1e 16 0.33 0.66 Receiver Input 0 25 50 75 100 125 150 175 200 time (ps) MSE = 6.12 10 3 0 25 50 75 100 125 150 175 200 time (ps) 10 Tap Transversal Equalizer Equalizer Input Equalizer Output 1 0.87 0.7 0.52 0.35 0.17 0 Equalizer Input 0.17 0 25 50 75 100 125 150 175 200 time (ps) 1.8 1.4 1.1 0.7 0.35 0 0.35 0.7 MSE = 2.77 10 3 0 25 50 75 100 125 150 175 200 time (ps) 10 Tap TW Equalizer

Summary-1 TWA FIR Filters represent the state-of-the-art in high speed equalization Signal attenuation due to double termination Need for an anti-alias" filter Delay cells are large and occupy space Example : A fully differential 10 tap TWA equalizer has 36 inductors! (each being about 300µm on a side Capacitive loading of lines reduces cut-off frequency of the delay lines TWA filters are not amenable to LMS adaptation

Summary-2 DFE used alongwith an FFE in tough channels - e.g. multimode channels. Timing recovery is an important issue. In simple channels, common to use an upfront timing recovery module that works with the receiver input. In more complicated channels, the FFE output can be used to derive the timing error. Joint timing recovery/equalization without a training sequence is a challenge.

Conclusions High speed equalization at multi-ghz datarates involves signal processing, circuit design and electromagnetics. The challenge is to implement well known signal processing techniques at such high data rates. Many problems to be solved - e.g. efficient LMS implementation at several GHz speeds. Lots of work to do!

Selected References Wu et. al, Integrated transversal equalizers in high-speed fiber-optic systems, IEEE JSSC, December 2003. Sewter et. al, A 3-tap FIR filter with cascaded distributed tap amplifiers for equalization up to 40 Gb/s, IEEE JSSC, August 2006. Pavan et. al, Nonidealities in Traveling Wave and Transversal FIR Filters Operating at Microwave Frequencies, IEEE TCAS-1, January 2006.