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Transcript of Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor:...
![Page 1: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/1.jpg)
Per-Tone Algorithms for ADSL Per-Tone Algorithms for ADSL TransceiversTransceivers
PhD-students: Koen Vanbleu, Geert Ysebaert
Supervisor: Marc Moonen
Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be
Presentation: ftp://ftp.esat.kuleuven.ac.be/sista/ysebaert/presentations/
KULeuven, ESAT SCD-SISTA, BelgiumKULeuven, ESAT SCD-SISTA, Belgium
October 22, 2002
![Page 2: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/2.jpg)
2
General OverviewGeneral Overview
• Basic Principles
• Per Tone Equalization
• Per Tone Echo Cancellation
• Per Tone Radio Frequency Interference (RFI) Mitigation
• Per Tone Crosstalk Mitigation
• Conclusions
![Page 3: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/3.jpg)
3
OverviewOverview
• Basic Principles
� Introduction
� DMT
– Transmitter structure
– Receiver structure
– Cyclic Prefix trick
� Data Model
• Principles
• Equalization
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 4: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/4.jpg)
4
IntroductionIntroduction
• Communication at high rates towards customer
� telephone wire, cable, fiber, wireless
• Communication over telephone wire
� Evolution: ever increasing bitrates
� E.g. Time to download 10 Mbyte file
• Principles– Intro– DMT– Data
model
• Equalization
• Echo
• RFI
• Crosstalk
• ConclusionsModem Time
56 Kbps
Voice band modem
24 minutes
128 Kbps ISDN 10 minutes
6 Mbps ADSL 13 seconds
52 Mbps VDSL 1.5 seconds
![Page 5: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/5.jpg)
5
IntroductionIntroduction
• Broadband communication over telephone line� ADSL (Asymmetric Digital Subscriber Line)
� VDSL (Very high bit rate Digital Subscriber Line)
� Bitrate is function of the line length
Upstream
Downstream
CustomerCentral
300 m6.4 Mbps52 MbpsVDSL
3 km640 Kbps6 MbpsADSL
Line lengthUpDown Frequency band
1.1 MHz
8.8 MHz
• Principles– Intro– DMT– Data
model
• Equalization
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 6: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/6.jpg)
6
• Traditional telephony (POTS) still available over the same wire.
DuplexingDuplexing
• Assign different frequency bins to up- and downstream directions� Frequency Division Duplexing (FDD)� Overlap: Echo Cancellation (EC)
f (kHz)
POTS UP DOWN POTS UP&DOWN
DOWN
4 25 138 1104 f (kHz)4 25 138 1104
e.g. ADSL
• Principles– Intro– DMT– Data
model
• Equalization
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 7: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/7.jpg)
7
Discrete Multi Tone: TransmitterDiscrete Multi Tone: Transmitter
00
11
10
01
Re
Im
2 bits
Re
Im
4 bits
bits Data symbols (QAM)
...
P/S
CP
kx
Cyclic Prefix
0
IFFT
N-point
.
.
.
.
.
.
...
IFFT modulation(Inverse Fast Fourier Transform)
N12/ N
• Principles– Intro– DMT– Data
model
• Equalization
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 8: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/8.jpg)
8
Discrete Multi Tone: ReceiverDiscrete Multi Tone: Receiver
00
11
10
01Re
Im
2 bits
Re
Im
4 bits
bits
Data symbols
ky...
S/P
CP
.
.
.
FFTN-point
FFT demodulation
.
.
.FEQ
1 tap / tone
.
.
.TEQ
tapsT
Time Domain
Equalizer
• Principles– Intro– DMT– Data
model
• Equalization
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 9: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/9.jpg)
9
Discrete Multi Tone: Cyclic PrefixDiscrete Multi Tone: Cyclic Prefix
To demodulator
`long’ channelCP
kkx
`short’ channel
kh
To demodulator
ky
• Principles– Intro– DMT– Data
model
• Equalization
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 10: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/10.jpg)
10
Discrete Multi Tone: InterferenceDiscrete Multi Tone: Interference
Influence of the channel behind the FFT:
• Short channel: amplitude- en phase change for each tone separately
Re
Im
Re
Im
Re
Im
iX iY iZ iH iH
• Long channel: interference between data symbols of different tones and different symbol periods)'( ii )'( kk
• Principles– Intro– DMT– Data
model
• Equalization
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 11: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/11.jpg)
11
Data modelData model
noisetransmitted data
symbols
IDFT-matrix
received samples add cyclic prefixFIR channel
synchronization
delay
nx
OO
OO
OO
sk
Tsk
kN
kN
kN
N
N
N
n
n
X
X
X
)1(
2
)1(:1
)(:1
)1(:1
ˆ
I
I
I
POO
OPO
OOP
O
h
h
O
y
0
0
)1(
2
sk
Tsk
y
y
1TN function of
Symbol lengthPrefix lengthEqualizer lengthSymbol period
NTk
• Principles– Intro– DMT– Data
model
• Equalization
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 12: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/12.jpg)
12
OverviewOverview
• Equalization
� “Pre FFT” Equalization– TEQ: several design algorithms
– See talk Prof. B. Evans
� “Post FFT” Equalization
– Equalization Per Tone
– Structure and Initialization
• Principles
• Equalization
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 13: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/13.jpg)
13
Time Domain Equalization (TEQ)Time Domain Equalization (TEQ)
Original structure of time domain equalizer + FEQs:
TEQ
kyS/P
CP
... FFT
FEQ
T taps
...
...
1 tap/tone
N-point
N
N
N
...N..
.- line with
down samplers
• Principles
• Equalization– TEQ– Per Tone
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 14: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/14.jpg)
14
TEQ: Channel ShorteningTEQ: Channel Shortening
• Channel Shortening [Al-Dhahir, Cioffi, Evans, Melsa, …]
⊖Finding `optimal’ TEQ leads to non-linear optimization
⊖Most channel shortening schemes are not equivalent to bitrate optimization
⊖Resulting bitrate is often sensitive to synchronization delay
⊖All tones are equalized in the same way limited capacity
⊕Limited memory: T-taps TEQ and 1-taps FEQ per used tone
• Principles
• Equalization– TEQ– Per Tone
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 15: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/15.jpg)
15
Per Tone Equalization (PTEQ)Per Tone Equalization (PTEQ)
y Y
• From TEQ to Equalization Per Tone [Van Acker]
)
TEQ
()(row
FEQtap1)( wY
NiiDk
iZ F
with Y an N x T Toeplitz matrix with received data samples
The received data symbol for tone i after equalization is given by
i
iD
TNi
ki
Z
w
wY
sFFT'
)(row)( F
After applying the associativity of the matrix product, we get
Equalization Per
Tone(PT-EQ)
• Principles
• Equalization– TEQ– Per Tone
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 16: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/16.jpg)
16
ky
S/P
N
N
N
...N
N
N
...1T
PT-EQ: StructurePT-EQ: Structure
• Efficient calculation with `sliding FFT’
• PTEQ-inputs: T successive FFT’s per DMT-symbol
• Cheap implementation using first FFT en T-1 real difference terms (t=2...T).
...
...
...
FFT
N-punt
T
FFTN-puntsliding
T –taps filter
w for each tone
PT-EQ ...
i
• Principles
• Equalization– TEQ– Per Tone
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 17: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/17.jpg)
17
PTEQ: StructurePTEQ: Structure
ky
N
N
N
...
N
... FFT
N-punt
...
1T
...
N N...
PTEQ ...
T –taps filter
v for each tonei
• PTEQ=linear combiner with T inputs per tone: 1 FFT-output and T-1 real difference terms
w vii
• Principles
• Equalization– TEQ– Per Tone
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 18: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/18.jpg)
18
PTEQ: ComplexityPTEQ: Complexity• Complexity during data transmission is comparable
with TEQ-complexity for the same T :
� TEQ
– 1 (real) T-taps TEQ @ sample frequency Fs
– 1 FFT operation @ symbol frequency Fs/(N+)
– (complex) 1-taps FEQ/used tone @ Fs/(N+)
� PTEQ
– 1 FFT operation @ Fs/(N+)
– (complex) T-taps PTEQ/used tone @ Fs/(N+)
(multiplications)
TEQ and FEQ PTEQ
O(Fs(T+1/2)+NlogN) O(Fs(T+1)+NlogN)
• Complexity reductions are possible by varying T per tone.
• PTEQ requires more memory than TEQ.
• Principles
• Equalization– TEQ– Per Tone
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 19: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/19.jpg)
19
PTEQ: InitializationPTEQ: Initialization
• Optimization of SNR with quadratic cost function per tone
• Direct initialization using channel and noise characteristics: Optimal MMSE solution per tone
Too expensive
• Adaptive initialization using training sequence minimization of the sum of quadratic errors
with LMS: convergence too slow with RLS: fast convergence, very complex with combination of RLS and LMS: fast convergence, lower complexity than full RLS [Ysebaert]
)(
1
2)()(T)( Ki
K
k
ki
kiii XJ vzvv
KkX ki 1,)(
• Principles
• Equalization– TEQ– Per Tone
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 20: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/20.jpg)
20
SimulationsSimulations
-40 -30 -20 -10 0 10 20 300
0.5
1
1.5
2
2.5
3
3.5x 10
6
Delay
Bit
rate
(bi
ts/s
)
32-taps PT-EQ8-taps PT-EQ32-taps TEQ8-taps TEQ
Comparison of PT-EQ and TEQ for 4km line, downstream
• Down: N=512, =32, Fs=2.2 MHz, tones 39-256
• Bitrate versus delay
• MMSE solution for PTEQ
• TEQ-init. with MMSE channel shortening with |b|=1
• Principles
• Equalization– TEQ– Per Tone
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 21: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/21.jpg)
21
SimulationsSimulations
Adaptive initialization T1.601#13line+24DSL NEXT, downstream
• Bitrate as a function of the number of training symbols for PT-EQ
• T=32, =-8
• Principles
• Equalization– TEQ– Per Tone
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 22: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/22.jpg)
22
OverviewOverview
• Echo cancellation (EC)
� Problem formulation
� Principles of EC
� Echo cancellation per tone (PTEC)
• Principles
• Equalization
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 23: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/23.jpg)
23
EC: Problem FormulationEC: Problem Formulation
• Hybrid couples transmitter and receiver to the same line
• Imperfectly balanced hybrid can cause leakage (echo) of the transmitted signal into the received signal.
• Solutions:
� Assign different frequencies for transmitted and received signal (FDD).
� Cancel the echo (EC).
DMT-tx
DMT-rx
hybrid echo-canceller
Echo
telephone line
• Principles
• Equalization
• Echo– Problem
formulation
– EC principle
– PTEC
• RFI
• Crosstalk
• Conclusions
![Page 24: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/24.jpg)
24
Principle of Echo CancellationPrinciple of Echo Cancellation
• Echo canceller has 2 tasks:� Modeling the echo path (adaptively).� Remove the estimate of the echo signal
from the received signal.• Original approaches:
- time domain EC (TEC)
- mixed time/frequency EC [Ho, Cioffi]
FEQ
N-IFFT CP P/S
N-FFT
CP
S/P
TEC
TEQ
hybride
• Principles
• Equalization
• Echo– Problem
formulation
– EC principle
– PTEC
• RFI
• Crosstalk
• Conclusions
![Page 25: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/25.jpg)
25
Per Tone Echo Cancellation Per Tone Echo Cancellation (PTEC)(PTEC)
• Structure [Van Acker]
Starting point: modem with equalization and echo cancellation in time domain (TEQ en TEC).
This structure is modified analogously to `TEQ to PT-EQ conversion’, i.e. TEQ and TEC are shifted behind FFT.
• Goal: bitrate optimization
)
TECTEQ
()(row
FEQtap1)(
ENiiDk
iZ wUwY
F
• Principles
• Equalization
• Echo– Problem
formulation
– EC principle
– PTEC
• RFI
• Crosstalk
• Conclusions
iE
iD
E
ET
Ni
i
iD
TNi
ki
Z
,sFFT'
)(row
sFFT'
)(row)(
w
wU
w
wY FF
![Page 26: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/26.jpg)
26
Per Tone Echo Cancellation Per Tone Echo Cancellation (PTEC)(PTEC)
N-FFTPTEC -line withdownsamp.
-line withdownsamp.
N-IFFT CP P/S
N-FFTPTEQ -line withdownsamp.
-line withdownsamp.
N1T
ky
ku
• Principles
• Equalization
• Echo– Problem
formulation
– EC principle
– PTEC
• RFI
• Crosstalk
• Conclusions
![Page 27: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/27.jpg)
27
PT-EC: ComplexityPT-EC: Complexity
• Complexity of PT-EC filtering
� Similar to time domain EC (for same filter length)
� Optimization of filter length per tone
� Extra FFT-operation on echo reference signal
• Cost function
� Cost function contains optimal joint shortening per tone
� SNR per tone is maximized
2)()(,
)(, ),( k
ik
iiEk
iiiEi XJ uvzvvv E
PT-ECPT-EQ
• Principles
• Equalization
• Echo– Problem
formulation
– EC principle
– PTEC
• RFI
• Crosstalk
• Conclusions
![Page 28: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/28.jpg)
28
SimulationsSimulations
Echo cancellation per tone for 4 km line, downstream
• FDM with tx- and rx-filters of low order
• Bitrate as a function of the length of the echo filter (PT-EC)
• Comparable with 400 taps time domain EC
02
2.2
2.4
2.6
2.8
3
3.2
3.4x 106
50 100 150 200 250T E
Bit
rate
(bi
ts/s
)
32-taps PTEQ2*16-taps PTEQ
32-taps PTEQ, no echo2*16-taps PTEQ, no echo
• Principles
• Equalization
• Echo– Problem
formulation
– EC principle
– PTEC
• RFI
• Crosstalk
• Conclusions
![Page 29: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/29.jpg)
29
OverviewOverview
• Radio frequency interference mitigation
� Problem definition
� Receiver structure (in brief)
Window incorporated PTEQ (WI-PTEQ)
� Simulation results
• Principles
• Equalization
• Echo
• RFI
• Crosstalk
• Conclusions
![Page 30: Per-Tone Algorithms for ADSL Transceivers PhD-students: Koen Vanbleu, Geert Ysebaert Supervisor: Marc Moonen Email: {moonen, vanbleu, ysebaert}@esat.kuleuven.ac.be.](https://reader037.fdocuments.us/reader037/viewer/2022110103/56649eec5503460f94bfe318/html5/thumbnails/30.jpg)
30
RFI interference problemRFI interference problem• Downstream band overlaps with e.g.
AM broadcast bands which causes narrowband interference.
� Contrary to popular belief: affects lots of tones
� Reason? High DFT filter bank side lobes.
� Solution? Windowing functions.
• Principles
• Equalization
• Echo
• RFI– Problem
formulation
– WI-PTEQ
• Crosstalk
• Conclusions
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PTEQ + windowing: Structure PTEQ + windowing: Structure [Cuypers]
• Principles
• Equalization
• Echo
• RFI– Problem
formulation
– WI-PTEQ
• Crosstalk
• Conclusions
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Simulation resultsSimulation results
• Nice gain for low number of tapsADSL T1.601#13 standard loop
RFI at 630, 740, 800, 980, 1100, 1160, 308 kHz
• Principles
• Equalization
• Echo
• RFI– Problem
formulation
– WI-PTEQ
• Crosstalk
• Conclusions
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OverviewOverview
• Per tone alien crosstalk mitigation
� Problem definition
� Principles of cyclostationarity
� Receiver structure
PTEQ combined with FRESH filtering
� Simulation results
• Principles
• Equalization
• Echo
• RFI
• Crosstalk
• Conclusions
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Problem Formulation: Problem Formulation: Per-tone Per-tone Alien Alien Crosstalk Crosstalk
MitigationMitigation• Crosstalk (XT)
Desired
Remote terminals
Central office
Binder
TX
RXRX
TX
TX TX
RX RX
User 1
User 2
Far-end XT
Near-end XT
• Principles
• Equalization
• Echo
• RFI
• Crosstalk– Problem
formulation
– Principle– Receiver
structure
• Conclusions
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Problem FormulationProblem Formulation
• Crosstalk (XT): reduces the SNR in each frequency bin
• Crosstalk types:� Self XT: caused by other ADSL systems
� Alien XT: caused by copper wire transmission systems with different modulation scheme occupying (partially) same frequency band
• Alien crosstalk examples:� in ADSL: HDSL and SDSL XT (baseband)
� in VDSL: HPNA (QAM passband)
• Principles
• Equalization
• Echo
• RFI
• Crosstalk– Problem
formulation
– Principle– Receiver
structure
• Conclusions
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kDSL symbol blocks
XT symbols
k+1 k+2
Non-integer relation between DSL and XT symbol rate
Principles of CyclostationarityPrinciples of Cyclostationarity
• What makes alien XT particular?
Sampling offset between DSL and XT changes from DSL block to block XT “nonstationary”, i.e. time varying, w.r.t. DSL symbol rate Processing varies from DSL block to block? No: exploit XT cyclostationarity(*) in “frequency domain” ((*) with large period: e.g. 100s of symbols)
• Principles
• Equalization
• Echo
• RFI
• Crosstalk– Problem
formulation
– Principle– Receiver
structure
• Conclusions
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Principles of CyclostationarityPrinciples of Cyclostationarity
• Received PSD of cyclostationary signals with excess bandwidth (EBW)
• E.g. SDSL XT, symbol rate of fs=1.04MHz, 100% EBW
• Principles
• Equalization
• Echo
• RFI
• Crosstalk– Problem
formulation
– Principle– Receiver
structure
• Conclusionsf
PSD(f)
fs/2 fs-fs/2-fs
EBWEBW
Same information about signal!
Determined by pulse shapeand channel
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Principles of CyclostationarityPrinciples of Cyclostationarity
• Mitigate the cyclostationary SDSL from a received signal y
f
PSD(f)
fs/2 fs
EBW + ADSL
by optimal combined filtering of y and frequency shifted version y’ (shift = fs) [Gardner]
y =
f
PSD(f)
fs/2 fs
EBW + shifted ADSLy’ =
uncorrelatedcorrelated
• Principles
• Equalization
• Echo
• RFI
• Crosstalk– Problem
formulation
– Principle– Receiver
structure
• Conclusions
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Receiver StructureReceiver Structure
• From classical TEQ to TEQ with alien crosstalk mitigation:
TEQyS/P
CP
... FFT FE
Q
...
...
1 tap/tone
N-points
)2exp( kfj s
XTcanceller'y
time invariant filtersOverall structure= time varying
• Principles
• Equalization
• Echo
• RFI
• Crosstalk– Problem
formulation
– Principle– Receiver
structure
• Conclusions
• Only prior knowledge required: fs=crosstalker symbol rate
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Per-Tone Receiver for Per-Tone Receiver for AlienAlien Crosstalk Mitigation Crosstalk Mitigation
• From “pre-FFT” to “post-FFT” (cfr. from TEQ to PTEQ)
N-FFT PTEQ-line withdownsamp.
-line withdownsamp.
N1T
y
)2exp( kfj s N-FFTXT
canceller
-line withdownsamp.
N
-line withdownsamp.
1T
• Principles
• Equalization
• Echo
• RFI
• Crosstalk– Problem
formulation
– Principle– Receiver
structure
• Conclusions
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Simulation ResultsSimulation Results
• Bitrate as a function of loop length (26AWG loops)
• SDSL crosstalker
• Up to 100 % gain around 3000m
• Principles
• Equalization
• Echo
• RFI
• Crosstalk– Problem
formulation
– Principle– Receiver
structure
• Conclusions
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ConclusionsConclusions
• Evolution in equalization
� TEQ: Simple initialization, low memory requirements, little relation with bit rate, unpredictable behaviour
� PTEQ: Optimize SNR per tone, comparable complexity, high memory requirements
• Per tone echo canceling
� PTEC: Optimize SNR per tone, apply the same trick as for PTEQ
• Radio frequency interference
� Solution based on PTEQ + windowing (WI-PTEQ)
• Crosstalk mitigation
� Solution based on PTEQ + FREquency SHift PTEQ (FRESH)
• Principles
• Equalization
•Echo
• RFI
• Crosstalk
• Conclusions
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Time-/frequency domain ECTime-/frequency domain EC
• Time-/frequency domain EC [Ho, Cioffi]
� Adaptation of EC filter: in frequency domain
� Removing echo: partially in time- and frequency domain
� Efficient implementation of time domain EC
N-IFFT
hybrid
freq. dom. EC
CP P/S
N-FFT CPS/P
Time dom. EC
TEQFEQ
• Principles
• Equalization
• Echo– Problem
formulation
– EC principle
– PTEC
• RFI
• Crosstalk
• Conclusions
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Double talk problemDouble talk problem
N-IFFT
hybrid
C P
N-FFT CP
CES
TEQFEQ
• Far end signal causes excess MSE in EC coefficient update
• LMS step size has to be lowered to average out far end signal reduced convergence speed = double talk problem
• Solution: cancellation of far end signal prior to EC update [Ysebaert]
Freq. ECUpdate1/FEQ
N-IFFT
• Principles
• Equalization
• Echo– Problem
formulation
– EC principle
– PTEC
• RFI
• Crosstalk
• Conclusions