alex g. olson, aditya chopra, yousof mortazavi, ian c. wong, and brian l. evans embedded signal...

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Real-Time MIMO Discrete Multitone Transceiver Testbed Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

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Page 1: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

Real-Time MIMO Discrete Multitone Transceiver Testbed

Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans

Embedded Signal Processing LaboratoryThe University of Texas at Austin

Page 2: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

IntroductionProblem Statement:

Single-channel wireline communications systems may not provide sufficient data rates for future telemetry applications

There is an upper limit to the communication bit rates depending on certain parameters :

Modulation and coding schemes Transmit Energy Receiver noise floor Transmission Bandwidth

Proposed SolutionUse multiple transceivers operating in parallel on different wires

Page 3: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

Discrete Multitone ModulationDMT is a commonly used modulation scheme in wireline communication systems (eg. DSL)The Idea:

Divide frequency selective channel into many narrowband subchannelsData is transmitted over each frequency flat subchannelFFT (Fast Fourier Transform) is used for modulation/demodulation

Page 4: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

MIMO DMT TestbedDesign Goal: Create a 2x2 DMT hardware testbed

Enables rapid prototyping/testing of new designs Provides user with complete control over system parameters Relatively unconstrained by resource and real-time issues Can be connected to different cable designs Allow visualization of the channel parameters and various communication performance

metrics

Benefits of Hardware TestbedConfigurable – User can choose system parameters and signal processing blocksAllows evaluation of the communication performance and computational

complexity tradeoffsCable modelling not required

Design ChallengesReal-time constraints on the transmitter and receiver systemAnalog front-end

Page 5: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

MIMO DMT System Model

NEXT: Near End CrosstalkPortion of the transmitted signal that leaks onto the local

receiver FEXT: Far End Crosstalk

Portion of the transmitted signal that leaks onto the remote receiver

Page 6: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

MIMO DMT System Model

Visualization and control

•Allow user to select system parameters•Display channel measurements and communication performance metrics•No real-time requirements

Transceiver

•Embedded PC running MIMO DMT communication system•Real-time requirements•D/A and A/D converters

Transmission Medium

•1000ft CAT-5e cable used as communication medium•Pairs of wires in the cable inter-twisted for maximum crosstalk•Measured FEXT ~ 10dB below signal level

Front-End•Hybrid circuits used for echo cancellation and as line drivers•Low-Pass filters to remove aliasing effects

Page 7: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

Modem Implementation- Hardware

TX0 TX1 RX0 RX1Embedded

PCPXI-8186

PXI Backplane - PXI-1045

LPF

H

LPF

H

LPF

H

LPF

H

PXI-5421 A/D PXI-5122 D/A

TCP Link

LPF : Low Pass FilterH: Hybrid

Page 8: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

Modem Implementation- SoftwareReal-Time Target

Baseband processing - C++ Dynamic Link Library (DLL)Generates/processes samples sent/received to/from NI

hardwareLabVIEW VIs

Accesses hardware and calls DLL functionsReal Time OS – ETOS is running on target to ensure

reatime performance

Desktop PCConnects to real-time target via TCP/IP linkVisualization and control using LabVIEW

Page 9: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

Bit AllocationFixed amount of energy available to transmit per DMT symbolDMT allows different number of bits transmitted on each toneBit Allocation can be adjusted to maximize throughput or the SNR

margin on each toneHughes Hartog Bit Allocation algorithm [D. Hughes-Hartog,1987]

implemented in the testbed

Unifom Gain Bit Allocation•Equal Power is allocated across all tones•Sub-optimal for frequency selective channels

Hughes Hartog Algorithm

•Greedy algorithm•One bit is added to the tone which requires least amount of energy

Uniform Power

Hughes-Hartog

0 0.2 0.4 0.6 0.8 1 1.2 1.4

Computational Complexity of Bit Allocation Algorithms

Execution Time in ms

Page 10: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

FEXT CancellationFar End Crosstalk provides significant amount of deterioration to the

bit rateUsing vectored DMT [Ginis and Cioffi,2002] the multiple receivers

are assumed to operate together to cancel crosstalkCrosstalk can be cancelled through linear and non linear receivers

The Zero Forcing equalizer is an example of a linear receiver with crosstalk cancellation

Successive Interference Cancellation is a non linear crosstalk cancellation receiver

Page 11: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

Slicer

Vectored DMT

11

QHYSuccessive

InterferenceCancellation

Estimate channelmatrix H

H = Q R

Training (per-tone)

• Uses channel estimate and both received signals to effectively cancel crosstalk

y0

y1

For each tone, “H”, “Q” and “R” are 2x2 matrices

Q RSymbol decoding

(per-tone)

Page 12: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

Experimental Results• System Parameters

• 256 tones per DMT symbol• Maximum Transmitted Voltage 5.0V• Receiver noise floor ~ -60dB

• 1000ft CAT-5 cable

• Inter-twisted pairs for maximum FEXT

• FEXT limits SNR to ~10dB

Page 13: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

Experimental Results

Page 14: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

ConclusionsFEXT (crosstalk) can be effectively cancelled with

Vectored DMT

Experimental tests show that a 2x2 Vectored DMT system achieves 1.99x data rate (~4Mbps) over single-channel DMT

Vectored DMT is practical and has low implementation cost (for 2x2 MIMO systems)

Hughes-Hartog bit loading (fine gains) can provide ~100Kbps data rate improvement over uniform gain

Page 15: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin
Page 16: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

D. Hughes-Hartog, ”Ensemble modem structure for imperfect transmission media.” U.S. Patents Nos. 4,679,227 (July 1987), 4,731,816 (March 1988), and 4,833,706 (May 1989)

G. Ginis and J. Cioffi, “Vectored transmission for digital subscriber line systems,” IEEE J. Select. Areas Commun., vol. 20, no. 5, pp. 1085-1104, Jun. 2002

Page 17: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

Hardware• National Instruments

– PXI Chassis– Embedded Computer– A/D and D/A boards– LabVIEW Real-Time

• Hardware + LabVIEW Real-Time form a 2x2 MIMO DMT modem

$25,000Total

$5,500PXI-5122114-Bit 100 MS/s Digitizer

$5,500PXI-5421216-Bit 100 MS/s AWG

$4,000PXI-81861Embedded Controller

$5,000PXI-10451PXI Chassis

Unit PricePart #Qty.Description

Equipment required for a uni-directional system:

Page 18: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

Analog Front-End

• Hybrid circuits from Texas Instruments– 4 x $50– Line Driver / “2-wire to 4-

wire” Interface

• Custom passive analog filters from TTE– 4x $275– Serve as anti-aliasing

filters for TX and RX

Page 19: Alex G. Olson, Aditya Chopra, Yousof Mortazavi, Ian C. Wong, and Brian L. Evans Embedded Signal Processing Laboratory The University of Texas at Austin

Modem Implementation

Embedded

PCTX 0 TX 1 RX 0 RX 1

DigitizerARB ARB

LPF

H

LPF

H

LPF

H

LPF

HARB: Arbitrary Waveform Generator

[Digital to Analog Converter]

Digitizer: [Analog to Digital Converter]

LPF: Low pass filter (anti-aliasing filter)

TC

P

PXI Chassis