High-Speed Wireline Communication Systems: Semester Wrap-up

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High-Speed WirelineCommunication Systems
Semester Wrap-up

• Ian C. Wong, Daifeng Wang, and
• Prof. Brian L. Evans
• Dept. of Electrical and Comp. Eng.The University
  of Texas at Austin
• http//signal.ece.utexas.edu

http//www.ece.utexas.edu/bevans/projects/adsl
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Outline

• Asymmetric Digital Subscriber Line (ADSL)
  Standards
• Overview of ADSL2 and ADSL2
• Data rate vs. reach improvements
• ADSL2
• Multichannel Discrete Multitone (DMT) Modulation
• Dynamic spectrum management
• Channel identification
• Spectrum balancing
• Vectored DMT
• System Design Alternatives and Recommendations

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1ADSL2 and ADSL2 - the new standards

• ADSL2 (G.992.3 or G.dmt.bis, and G.992.4 or
  G.lite.bis)
• Completed in July 2002
• Minimum of 8 Mbps downstream and 800 kbps
  upstream
• Improvements on
• Data rate vs. reach performance
• Loop diagnostics
• Deployment from remote cabinets
• Spectrum and power control
• Robustness against loop impairments
• Operations and Maintenance
• ADSL2 (G.992.5)
• Completed in January 2003
• Doubles bandwidth used for downstream data (20
  Mbps at 5000 ft)

1Figures and text are extensively referenced from
ADSL2 ADSL2white
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Data rate vs. reach performance improvements

• Focus long lines with narrowband interference
• Achieves 12 Mbps downstream and 1 Mbps upstream
• Accomplished through
• Improving modulation efficiency
• Reducing framing overhead
• Achieving higher coding gain
• Employing loop bonding
• Improving initialization state machine
• Online reconfiguration

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1. Improved Modulation Efficiency

• Mandatory support of Trellis coding (G.992.3,
  8.6.2)
• Block processing of Wei's Wei87 16-state
  4-dimensional trellis code shall be supported to
  improve system performance
• Note There was a proposal in 1998 by Vocal to
  use a Parallel concatenated convolutional code
  (PCCC), but it wasnt included in the standard
  (http//www.vocal.com/white_paper/ab-120.pdf)
• Data modulated on pilot tone (optional, 8.8.1.2)
• During initialization, the ATU-R receiver can set
  a bit to tell the ATU-C transmitter that it wants
  to use the pilot-tone for data
• The pilot-tone will then be treated as any other
  data-carrying tone
• Mandatory support for one-bit constellations
  (8.6.3.2)
• Allows poor subchannels to still carry some data

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2. Reduced framing overhead

• Programmable number of overhead bits (7.6)
• Unlike ADSL where overhead bits are fixed and
  consume 32 kbps of actual payload data
• In ADSL2, it is programmable between 4-32 kbps
• In long lines where data rate is low, e.g. 128
  kbps,
• ADSL 32/128 25 is overhead
• ADSL2 as low as 4/128 3.125 is overhead

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3. Achieved higher coding gain

• On long lines where data rates are low, higher
  coding gain from the Reed-Solomon (RS) code can
  be achieved
• Flexible framing allows RS code to have
  (7.7.1.4)
• 0, 2, 4, 6, 8, 10, 12, 14, or 16 redundancy
  octets
• 0 redundancy implies no coding at all (for very
  good channels)
• 16 would achieve the highest coding gain at the
  expense of higher overhead (for very poor
  channels)

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4. Loop Bonding

• Supported through Inverse Multiplexing over ATM
  (IMA) standard (ftp//ftp.atmforum.com/pub/approve
  d-specs/af-phy-0086.001.pdf)
• Specifies a new sublayer (framing, protocols,
  management) between Physical and ATM layer
  IMA99

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5. Improved initialization state machine

• Power cutback
• Reduction of transmit power spectral density
  level in any one direction
• Reduce near-end echo and the overall crosstalk
  levels in the binder
• Receiver determined pilots
• Avoid channel nulls from bridged taps or narrow
  band interference from AM radio
• Initialization state length control
• Allow optimum training of receiver and
  transmitter signal processing functions
• Spectral shaping
• Improve channel identification for training
  receiver time domain equalizer during Channel
  Discovery and Transceiver Training phases
• Tone blackout (disabling tones)
• Enable radio frequency interference (RFI)
  cancellation schemes

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6. Online reconfiguration (10.2)

• Autonomously maintain operation within limits set
  by control parameters
• Useful when line or environment conditions are
  changing
• Optimise ATU settings following initialization
• Useful when employing fast initialization
  sequence that requires making faster estimates
  during training
• Types of online reconfiguration
• Bit swapping
• Reallocates data and power among the subcarriers
• Dynamic rate repartitioning (optional)
• Reconfigure the data rate allocation between
  multiple latency paths
• Seamless rate adaptation (optional)
• Reconfigure the total data rate

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ADSL2 (G.992.5)

• Doubles the downstream bandwidth
• Significant increase in downstream data rates on
  shorter lines

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Outline

• Asymmetric Digital Subscriber Line (ADSL)
  Standards
• Overview of ADSL2 and ADSL2
• Data rate vs. reach improvements
• ADSL2
• Multichannel Discrete Multitone (DMT) Modulation
• Dynamic spectrum management
• Channel identification
• Spectrum balancing
• Vectored DMT
• System Design Alternatives and Recommendations

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Dynamic Spectrum Management

• Allows adaptive allocation of spectrum to various
  users in a multiuser environment
• Function of the physical-channel
• Used to meet certain performance metrics
• One can treat each DMT receiver as a separate
  user
• Better than static spectrum management
• Adapts to environment rather than just designing
  for worst-case
• E.g. ADSL used static spectrum management (Power
  Spectral Density Masks) to control crosstalk
• Too conservative limited rates vs. reach

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Dynamic Spectrum Management

• Channel Identification Methods
• Initialization and training
• Estimation of the channel transfer function
• Spectrum Balancing
• Distributed power control (iterative
  waterfilling)
• Centralized power control (optimal spectrum
  management)
• Vectored Transmission Methods

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Training Sequences

• Training Sequence
• Goal estimate the channel impulse response
  before data transmission
• Type periodic or aperiodic, time or frequency
  domain
• Power spectrum approximately flat over the
  transmission bandwidth
• Design optimize sequence autocorrelation
  functions
• Perfect Training Sequence
• All of its out-of-phase periodic autocorrelation
  terms are 0 1
• Suggested training sequences for DMT
• Pseudo-random binary sequence with N samples
• Periodic by repeating N samples or adding a
  cyclic prefix

1 W. H. Mow, A new unified construction of
perfect root-of-unity sequences, in Proc.
Spread-Spectrum Techniques and Applications, vol.
3, 1996, pp. 955959.
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Training Sequences

• y S h n
• h L-tap channel
• S transmitted N x L Toeplitz matrix made up of N
  training symbols
• n additive white Gaussian noise (AWGN)

MIMO is multiple-input multiple-output
Domain Method Minimum MSE Complexity Optimal Sequence
Time Periodic (LS)1 Yes High (2N) Yes
Time Aperiodic 2 No Medium (N2) Yes
Time L-Perfect (MIMO) 3 Almost Low (N log2N) Sometimes
Frequency Periodic 4 No Low (N log2N) Sometimes
impulse-like autocorrelation and zero
crosscorrelation
1 W. Chen and U. Mitra, "Frequency domain
versus time domain based training sequence
optimization," in Proc. IEEE Int. Conf. Comm.,
pp. 646-650, June 2000. 2 C. Tellambura, Y. J.
Guo, and S. K. Barton, "Channel estimation using
aperiodic binary sequence," IEEE Comm. Letters,
vol. 2, pp. 140-142, May 1998. 3 C. Fragouli,
N. Al-Dhahir, W. Turin, Training-Based Channel
Estimation for Multiple-Antenna Broadband
Transmissions," IEEE Trans. on Wireless Comm.,
vol.2, No.2, pp 384-391, March 2003 4 C.
Tellambura, M. G. Parker, Y. Guo, S . Shepherd,
and S . K. Barton, Optimal sequences for channel
estimation using Discrete Fourier Transform
techniques, IEEE Trunsuctions on Communicutions,
vol.47, no.2, pp. 230-238, Feb. 1999
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Training-Based Channel Estimation for MIMO

• 2 x 2 MIMO Model

Duplex Channel
TX 1
RX 1
h11
h12
h21
TX 2
RX 2
h22
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Crosstalk Estimation

• Noises are unknown crosstalkers and
  thermal/radio
• Power spectral density N(f)
• Frequency bandwidth of measurement
• Time interval for measurement
• Requisite accuracy
• Channel ID 1
• Estimate gains at several frequencies
• Estimate noise variances at same frequencies
• SNR is then gain-squared/noise estimate
• Basic MIMO crosstalk ID
• Near-end crosstalk (NEXT)
• Far-end crosstalk (FEXT)

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Spectrum Balancing

• Decides the spectral assignment for each user
• Allocation is based on channel line and signal
  spectra
• For single-user, water-filling is optimal
• For the multiuser case, performance evaluation
  and/or optimization becomes much more complex
• Methods
• Distributed power control
• No coordination at run-time required
• Set of data rates must be predetermined
• Centralized power control
• Coordination at central office (CO) transmitter
  is required

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Distributed Multiuser Power Control
Yu, Ginis, Cioffi, 2002

• Iterative waterfilling approach

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Centralized Optimal Spectrum Management
Cendrillon, Yu, Moonen, Verlinden, Bostoen, to
appear

• Rate-adaptive problem with rate constraints

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Comparison among methods
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Vectored Transmission Methods

• Signal level coordination
• Full knowledge of downstream transmitted signal
  and upstream received signal at central office
• Block transmission at both ends fully
  synchronized
• Channel characterization
• MIMO on a per-tone basis

DS-Precoding
RT
CO
US-Successive Crosstalk-Cancellation
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Upstream Successive Crosstalk Cancellation
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Downstream MIMO Precoding

• We can also use Tomlinson-Harashima
  precoding(as used in High-speed DSL) to prevent
  energy increase

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Comments

• Because of limited computational power at
  downstream Tx (reverse of that in typical
  DSL/Wireless systems)
• Successive crosstalk cancellation at Rx makes
  more sense
• Do the QR decomposition also at Rx
• Dont need to feedback channel information, since
  it is used at the receiver only
• Transmit optimization procedures can also be done
  at Rx
• It is actually simpler since we can assume that
  the cross-talk is cancelled out
• Just do single-user waterfilling for each
  separate user (loop)
• Optimal power allocation settings fed back to
  transmitter

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Outline

• Asymmetric Digital Subscriber Line (ADSL)
  Standards
• Overview of ADSL2 and ADSL2
• Data rate vs. reach improvements
• ADSL2
• Multichannel Discrete Multitone (DMT) Modulation
• Dynamic spectrum management
• Channel identification
• Spectrum balancing
• Vectored DMT
• System Design Alternatives and Recommendations

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Training-Based Channel Estimation for MIMO

• Linear Least Squares
• Low complexity but enhances noise. Assumes S has
  full column rank
• MMSE
• zero-mean and white Gaussian noise
• Sequences satisfy above are optimal sequences
• Optimal sequences impulse-like autocorrelation
  and zero crosscorrelation

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Simple Channel Estimation for MIMO

• How to design s1(L,Nt) and s2(L,Nt) ?
• Simple and intuitive method ( 2 X 2 )
• Sending the training data at only one TX( turn
  off another TX) during one training time slot,
  i.e.
• Very Low Complexity and even No Need to Design
  Training Sequences
• But Time Consuming
• Design training sequences to estimate the channel
  during one training time slot

Method Computational Complexity Time
Simple Low High
Design TS High Low
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Design Training Sequences for MIMO

• Recommendation Design Method I
• Design instead a single training sequence s (2L,
  NtL1)
• s1s(0)s(Nt), s2s(L)s(NtL)
• MMSE but High searching complexity
• Recommendation Design Method II
• A sequence s produces s1 and s2 with 0 cross
  correlation by encoding
• Lower MSE and Only s with good auto-correlation
  properties
• Trellis Code
• Block Code
  time-reversing
• 
  complex
  conjugation

Method Computational Complexity MMSE
I High Yes
II Low Almost
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Choice of Multichannel Method

• Choice of methods is a performance-complexity
  tradeoff
• Loop bonding simplest to implement, but poor
  performance
• Spectrum balancing methods
• Iterative waterfilling at the receiver can be
  implemented pretty easily
• Pre-determine target rates through offline
  analysis
• No coordination needed among the loops
• Just feedback the power allocation settings to
  corresponding Tx
• Optimal spectrum management
• We can simply maximize rate-sum (all weights1)
• Coordination at Rx is needed (jointly optimize
  across loops)
• Vectored transmission
• Coordination on both sides are required
• Run-time complexity is not too bad O(K3)
  QR-Decomposition only need to be done at training
• Transmit optimization is also simpler than
  spectrum balancing methods

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Comparison
Loop Bonding Iterative Waterfilling Optimal Spectrum Balancing Vectored-DMT
Design Complexity Low Medium Medium High
Computational Complexity Low Medium Very high High
Coordination Required Low Medium High Very high
Data-rate performance Low Medium High Very High
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Backup Slides
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ADSL2 improvements over ADSL

• Application-related features
• Improved application support for an all digital
  mode of operation and voice over ADSL operation
• Packet TPS-TC1 function, in addition to the
  existing Synchronous Transfer Mode (STM) and
  Asynchronous TM (ATM)
• Mandatory support of 8 Mbit/s downstream and 800
  kbit/s upstream for TPS-TC function 0 and frame
  bearer 0
• Support for Inverse Multiplexing for ATM (IMA) in
  the ATM TPS-TC
• Improved configuration capability for each TPS-TC
  with configuration of latency, BER and minimum,
  maximum and reserved data rate.

1Transport Protocol Specific-Transmission
Convergence
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ADSL2 improvements over ADSL (cont.)

• PMS-TC1 related features
• A more flexible framing, including support for up
  to 4 frame bearers, 4 latency paths
• Parameters allowing enhanced configuration of the
  overhead channel
• Frame structure with
• Receiver selected coding parameters
• Optimized use of RS coding gain
• Configurable latency and bit error ratio
• OAM2 protocol to retrieve more detailed
  performance monitoring information
• Enhanced on-line reconfiguration capabilities
  including dynamic rate repartitioning.

1 Physical Media Specific-Transmission
Convergence 2 Operations, Administration, and
Maintenance
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ADSL2 improvements over ADSL (cont.)

• Physical Media Dependent (PMD) related features
• New line diagnostics procedures for both
  successful and unsuccessful initialization
  scenarios, loop characterization and
  troubleshooting
• Enhanced on-line reconfiguration capabilities
  including bitswaps and seamless rate adaptation
• Optional short initialization sequence for
  recovery from errors or fast resumption of
  operation
• Optional seamless rate adaptation with line rate
  changes during showtime
• Improved robustness against bridged taps with RX
  determined pilot
• Improved transceiver training with exchange of
  detailed transmit signal characteristics
• Improved SNR measurement during channel analysis
• Subcarrier blackout to allow RFI measurement
  during initialization and SHOWTIME
• Improved performance with mandatory support of
  trellis coding, one-bit constellations, and
  optional data modulated on the pilot-tone

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ADSL2 improvements over ADSL (cont.)

• PMD related features (cont.)
• Improved RFI robustness with receiver determined
  tone ordering
• Improved transmit power cutback possibilities
• Improved Initialization with RX/TX controlled
  duration of init. states
• Improved Initialization with RX-determined
  carriers for modulation of messages
• Improved channel identification capability with
  spectral shaping during Channel Discovery and
  Transceiver Training
• Mandatory transmit power reduction to minimize
  excess margin under management layer control
• Power saving feature with new L2 low power state
  and L3 idle state
• Spectrum control with individual tone masking
  under operator control through CO-Management
  Information Base
• Improved conformance testing including increase
  in data rates for many existing tests.

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Bibliography

• ADSL2 ITU-T Standard G.992.3, Asymmetric
  digital subscriber line transceivers 2 (ADSL2),
  Feb. 2004
• ADSL2white ADSL2 and ADSL2plus-The new ADSL
  standards. Online http//www.dslforum.org/aboutd
  sl/ADSL2_wp.pdf, Mar. 2003
• Wei87 L.-F.Wei, Trellis-coded modulation with
  multidimensional constellations, IEEE Trans.
  Inform. Theory, vol. IT-33, pp. 483-501, July
  1987.
• IMA99 ATM Forum Specification af.phy-0086.001,
  Inverse Multiplexing for ATM (IMA), Version 1.1.,
  Mar. 1999