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High-Speed Wireline Communication 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. Outline.

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high speed wireline communication systems semester wrap up

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

outline
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
1 adsl2 and adsl2 the new standards
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]

data rate vs reach performance improvements
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
1 improved modulation efficiency
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 wasn’t 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
2 reduced framing overhead
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
3 achieved higher coding gain
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)
4 loop bonding
4. Loop Bonding
  • Supported through Inverse Multiplexing over ATM (IMA) standard (ftp://ftp.atmforum.com/pub/approved-specs/af-phy-0086.001.pdf)
    • Specifies a new sublayer (framing, protocols, management) between Physical and ATM layer [IMA99]
5 improved initialization state machine
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
6 online reconfiguration 10 2
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
adsl2 g 992 5
ADSL2+ (G.992.5)
  • Doubles the downstream bandwidth
  • Significant increase in downstream data rates on shorter lines
outline12
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
dynamic spectrum management
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
dynamic spectrum management14
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
training sequences
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. 955–959.

training sequences16
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

* 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

training based channel estimation for mimo
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

crosstalk estimation
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)
spectrum balancing
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
distributed multiuser power control
Distributed Multiuser Power Control

[Yu, Ginis, & Cioffi, 2002]

  • Iterative waterfilling approach
centralized optimal spectrum management
Centralized Optimal Spectrum Management

[Cendrillon, Yu, Moonen, Verlinden, & Bostoen, to appear]

  • Rate-adaptive problem with rate constraints
vectored transmission methods

Tx

Rx

Rx

Tx

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

upstream successive crosstalk cancellation

=

+

K vector of

received samples

K£K MIMO

channel matrix for tone i

=

+

uncorrelated components

Upstream: Successive Crosstalk Cancellation
downstream mimo precoding

Transmitted signal

Original symbols

£

Channel

=

Received signal

crosstalk-free

Downstream: MIMO Precoding
  • We can also use Tomlinson-Harashima precoding(as used in High-speed DSL) to prevent energy increase
comments
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
      • Don’t 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
outline27
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
training based channel estimation for mimo28
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
simple channel estimation for mimo
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
design training sequences for mimo
Design Training Sequences for MIMO
  • Recommendation Design Method I
    • Design instead a single training sequence s (2L, Nt+L+1)
    • s1=[s(0)…s(Nt)], s2=[s(L)…s(Nt+L)]
    • 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

choice of multichannel method
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 weights=1)
      • 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
adsl2 improvements over adsl
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

adsl2 improvements over adsl cont
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

adsl2 improvements over adsl cont36
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
adsl2 improvements over adsl cont37
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.
bibliography
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/aboutdsl/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

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