Modem Design, Implementation, and Testing Using NI

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Modem Design, Implementation, and Testing Using
NIs LabVIEW

• Prof. Brian L. Evans
• Embedded Signal Processing Laboratory
• The University of Texas at Austin
• bevans_at_ece.utexas.edu

Contributions by Vishal Monga, Zukang Shen, Ahmet
Toker, and Ian Wong, UT Austin
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Outline

• Real-Time DSP Course
• Single Carrier Transceiver
• Sinusoidal Generation
• Digital Filters
• Data Scramblers
• Pulse Amplitude Modulation
• Quadrature Amplitude Modulation
• Multicarrier Transceiver
• Conclusion

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Real-Time DSP Course Overview

• Objectives of junior-level class
• Build intuition for signal processing concepts
• Translate signal processing concepts
  intoreal-time digital communications software
• Lecture breadth (three hours/week)
• Digital signal processing algorithms
• Digital communication systems
• Digital signal processor architectures
• Laboratory depth (three hours/week)
• Deliver voiceband modem
• Design is the science of tradeoffs (Yale Patt)
• Test/validate implementation

Over 500 served since 1997
http//www.ece.utexas.edu/bevans/courses/realtime
/
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Real-Time DSP Course Which DSP?

• Students are third-year undergraduates
• Fixed-point DSPs for high-volume products
• Battery-powered cell phones, digital still
  cameras
• Wall-powered ADSL modems, cellular basestations
  
• Fixed-point issues
• Using non-standard C extensions for fractional
  data
• Converting floating-point programs to fixed-point
• Manual tracking of binary point prone to error
• Floating-point DSPs
• Feasibility for fixed-point DSP realization
• Shorter prototyping time
• Program TI TMS320C67x DSP in C
• Code Composer Studio 2.2

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Real-Time DSP Course Textbooks

• C. R. Johnson, Jr., and W. A.Sethares,
  TelecommunicationBreakdown, Prentice Hall, 2004.
• Intro to digital communicationsand transceiver
  design
• Matlab examples
• S. A. Tretter, Comm. System Design usingDSP
  Algorithms with Lab Experiments forthe
  TMS320C6701 TMS320C6711, 2003.
• Assumes DSP theory and algorithms
• Assumes access to C6000 reference manuals
• Errata/code http//www.ece.umd.edu/tretter

Rick Johnson (Cornell)
Bill Sethares (Wisconsin)
Steven Tretter (Maryland)
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Lab 1. QAM Transmitter Diagram
Lab 4Rate Control
LabVIEW demo by Zukang Shen (UT Austin)
Lab 6 QAM Encoder
Lab 2 PassbandSignal
Lab 3Tx Filters
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Lab 1. QAM Transmitter Diagram
LabVIEW Control Panel
QAM Passband Signal
Eye Diagram
LabVIEW demo by Zukang Shen (UT Austin)
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Lab 1. QAM Transmitter Diagram
passband signal for 1200 bps mode
square root raise cosine, roll-off 0.75, SNR ?
passband signal for 2400 bps mode
raise cosine, roll-off 1, SNR 30 dB
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Lab 2. Sine Wave Generation

• Aim Evaluate three waysto generate sine waves
• Function call
• Lookup table
• Difference equation
• Three output methods
• Polling data transmit register
• Software interrupts
• Direct memory access (DMA) transfers
• Expected outcomes are to understand
• Signal quality vs. implementation complexity
  tradeoff
• C6701 EVM boards stereo codec operation
• Interrupt mechanisms and DMA transfers

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Lab 2. Sine Wave Generation

• Evaluation procedure
• Validate sine wave frequency on scope, and test
  for various sampling rates (14 sampling rates on
  board)
• Method 1 with interrupt priorities
• Method 1 with different DMA initialization(s)

Spring 2004
Fall 2003HP 60 MHz Digital Storage Oscilloscope
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Lab 3. Digital Filters

• Aim Evaluate four ways to implementdiscrete-time
  linear time-invariant filters
• FIR filter convolution in C and assembly
• IIR Filter direct form and cascade of biquads,
  both in C
• IIR filter design gotchas oscillation
  instability
• In classical designs, poles sensitive to
  perturbation
• Quality factor measures sensitivity of pole pair
  Q ? ½ , ? ) where Q ½ dampens and Q ?
  oscillates
• Elliptic analog lowpass IIR filter dp 0.21 at
  wp 20 rad/s and ds 0.31 at ws 30 rad/s
  Evans 1999

Q poles zeros
1.7 -5.3533j16.9547 0.0j20.2479
61.0 -0.1636j19.9899 0.0j28.0184
Q poles zeros
0.68 -11.4343j10.5092 -3.4232j28.6856
10.00 -1.0926j21.8241 -1.2725j35.5476
optimized
classical
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Lab 3. Digital Filters

• IIR filter design for implementation
• Butterworth/Chebyshev filters specialcases of
  elliptic filters
• Minimum order not always most efficient
• Filter design gotcha polynomial inflation
• Polynomial deflation (rooting) reliable in
  floating-point
• Polynomial inflation (expansion) may degrade
  roots
• Keep native form computed by filter design
  algorithm
• Expected outcomes are to understand
• Speedups from convolution assembly routine vs. C
• Quantization effects on filter stability (IIR)
• FIR vs. IIR how to decide which one to use

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Lab 3. Digital Filters

• Test Equipment
• Agilent Function Generator
• HP 60 MHz Digital Storage Oscilloscope
• Spectrum Analyzer
• Evaluation Procedure
• Sweep filters with sinusoids to construct
  magnitude and phase responses
• Manually using test equipment, or
• Automatically by LabVIEW DSP Test Integration
  Toolkit
• Check filter output for cut-off frequency,
  roll-off factor
• FIR Compare execution times (in Code Composer)
  of
• C without compiler optimizations
• C with compiler optimizations
• C callable assembly language routine
• IIR Compute execution times (in Code Composer)

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Lab 4. Data Scramblers

• Aim Generate pseudo-random bit sequences
• Build data scrambler for given connection
  polynomial
• Descramble data via descrambler
• Obtain statistics of scrambled binary sequence
• Expected outcomes are to understand
• Principles of pseudo-noise (PN) sequence
  generation
• Identify applications in communication systems

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Lab 4. Data Scramblers

• Evaluation procedure
• Check scrambler output for various deterministic
  sequences as input(s)
• Descrambler must recover input sequence from
  scrambled one
• Test for sequence period, autocorrelation and
  other significant statistical properties
• Using DSP Test Measurement Toolkit instead
• Compute autocorrelation of PN sequence
• Compare this autocorrelation with that of white
  noise generated by LabVIEW to measue PN sequence
  quality

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Lab 5. Digital PAM Transceiver

• Aim Develop PAM transceiver blocks in C
• Amplitude mapping to PAM levels
• Interpolation filter bank for pulse shaping
  filter
• Clock recovery via phase locked loops

L samples per symbol
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Lab 5. Digital PAM Transceiver

• Expected Outcomes are to understand
• Basics of PAM modulation
• Zero inter-symbol interference condition
• Clock synchronization issues
• Test Equipment Same as Lab 3
• Evaluation Procedure
• Generate eye diagram to visualize PAM signal
  quality
• Observe spectrum of modulated signal
• Prepare DSP modules to test symbol clock
  frequency recovery subsystem

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Lab 6. Digital QAM Transmitter

• Aim Develop QAM transmitter blocks in C
• Differential encoding of digital data
• Constellation mapping to QAM levels
• Interpolation filter bank for pulse shaping filter

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Lab 6. Digital QAM Transmitter

• Expected outcomes are to understand
• In-phase and quadrature modulation principles
• Bandwidth efficiency issues
• Test equipment same as Lab 5
• Evaluation procedure
• Verify differential encoding and QAM mapping
• Generate eye diagram to visualize QAM signal
  quality
• Observe spectrum of modulated signal

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Lab 7. Digital QAM Receiver Part 1

• Aim Develop QAM receiver blocks in C
• Carrier recovery
• Coherent demodulation
• Decoding of QAM levels to digital data
• Expected outcomes are to understand
• Carrier detection and phase adjustment
• Design of receive filter
• Probability of error analysis to evaluate decoder
• Test equipment Same as Lab 6
• Evaluation procedure
• Recover and display carrier on scope
• Regenerate eye diagram and QAM constellation
• Observe signal spectra at each decoding stage

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Developed Voiceband Transceiver Now What? Got
Anything Faster?

• Multicarrier modulation divides broadband channel
  into narrowband subchannels
• No inter-symbol interference if constant
  subchannel gain and ideal sampling
• Based on fast Fourier transform (FFT)
• ADSL/VDSL and IEEE 802.11a/g 802.16a

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Multicarrier Modulation by IFFT
Q
g(t)
x
x
I
Discrete time
g(t)
x
x


g(t)
x
x
g(t) pulse shaping filter Xi ith
symbol from encoder
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Multicarrier Modulation (ADSL)
QAM Mapping
00101
N/2 subchannels (carriers)
N real-valuedtimesamplesformsADSLsymbol
Mirror complex data (in blue) andtake conjugates
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Multicarrier Modulation (ADSL)
Inverse FFT
CP Cyclic Prefix
D/A transmit filter
ADSL frame is an ADSL symbol plus cyclic prefix
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Multicarrier Demodulation (ADSL)
S/P
N-point FastFourierTransform(FFT)
N/2 subchannels (carriers)
N time samples
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ADSL Transceiver Data Xmission
2.208 MHz
N/2 subchannels
N real samples
S/P
quadrature amplitude modulation (QAM) encoder
mirror data and N-IFFT
add cyclic prefix
P/S
D/A transmit filter
Bits
00110
TRANSMITTER
each block programmed in lab and covered in one
full lecture
channel
each block covered in one full lecture
RECEIVER
N real samples
N/2 subchannels
P/S
time domain equalizer (FIR filter)
QAM decoder
N-FFT and remove mirrored data
S/P
remove cyclic prefix
receive filter A/D
invert channel frequency domain equalizer
P/S parallel-to-serial S/P
serial-to-parallel FFT fast Fourier transform
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Telecom and University Tracks

• Modem Design, Implementation, and Testing Using
  NIs LabVIEW

Dr. Brian L. Evans Associate Professor The
University of Texas at Austin bevans_at_ece.utexas.ed
u