Download
high speed wireline communication systems semester wrap up n.
Skip this Video
Loading SlideShow in 5 Seconds..
High-Speed Wireline Communication Systems: Semester Wrap-up PowerPoint Presentation
Download Presentation
High-Speed Wireline Communication Systems: Semester Wrap-up

High-Speed Wireline Communication Systems: Semester Wrap-up

330 Vues Download Presentation
Télécharger la présentation

High-Speed Wireline Communication Systems: Semester Wrap-up

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. 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

  2. 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

  3. 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]

  4. 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

  5. 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

  6. 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

  7. 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)

  8. 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]

  9. 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

  10. 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

  11. ADSL2+ (G.992.5) • Doubles the downstream bandwidth • Significant increase in downstream data rates on shorter lines

  12. 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

  13. 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

  14. 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

  15. 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.

  16. 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

  17. 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

  18. 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)

  19. 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

  20. Distributed Multiuser Power Control [Yu, Ginis, & Cioffi, 2002] • Iterative waterfilling approach

  21. Centralized Optimal Spectrum Management [Cendrillon, Yu, Moonen, Verlinden, & Bostoen, to appear] • Rate-adaptive problem with rate constraints

  22. 10K ft CO 10K ft RT 7K ft Comparison among methods

  23. 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

  24. = + K vector of received samples K£K MIMO channel matrix for tone i = + uncorrelated components Upstream: Successive Crosstalk Cancellation

  25. 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

  26. 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

  27. 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

  28. 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

  29. 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

  30. 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

  31. 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

  32. Comparison

  33. Backup Slides

  34. 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

  35. 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

  36. 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

  37. 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.

  38. 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