Texas Instruments Linearization Fundamentals Driving Digital Pre-Distortion and the GC5322! - PowerPoint PPT Presentation

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Texas Instruments Linearization Fundamentals Driving Digital Pre-Distortion and the GC5322!

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Title: Texas Instruments Linearization Fundamentals Driving Digital Pre-Distortion and the GC5322!


1
Texas InstrumentsLinearization Fundamentals
Driving Digital Pre-Distortionand the GC5322!
April 2006
2
Agenda
  • Introduction and Impact
  • Origin and History of the Problem
  • Linearization Fundamentals
  • Polynomial Power Amplifier Modeling
  • Crest Factor Reduction
  • Digital Pre-Distortion
  • System Implementation
  • Crest Factor Reduction and Digital Pre-Distortion
  • Adaptive Memory Pre-distortion of Power
    Amplifiers
  • Conclusions

3
Introduction and Impact
  • The demands for spectrally efficient modulation
    schemes have increased however these schemes are
    subject to severe intermodulation distortion
    (IMD) when the power amplifiers (PA) are operated
    near saturation
  • Unfortunately, PAs are most efficient when
    operated near saturation

Super 3G 4G
20MHz BW_at_ 2.1GHz
WiMAX .16a/d/e
10-40MHz BW _at_ 2.5, 3.5 5GHz
WCDMA
5MHz BW_at_ 2.1GHz
Cellular Channel BW _at_ Band
Increased signal bandwidth and complexity
CDMA 2000
1.25MHz BW _at_ 1.9GHz
A big challenge forMCPA designers!
EDGE/ CDMA
200kHz BW _at_ 800MHz
TDMA/ GSM
lt200kHz BW _at_ 8-900MHz
AMPS/ D-AMPS
30kHz BW _at_ 800MHz
4
Introduction and Impact
  • High Power RF PAs (gt10W) use multiple driver
    stages to amplify an input signal.
  • Different PA architectures (Class A, AB, C, etc
    ) offer various degrees of linearity, cost and
    efficiency.
  • RF PAs are notoriously inefficient Air is a
    convenient but poor transmission medium.
  • RF PAs are designed (tuned) for specific
    frequency range and bandwidth
  • MCPA wideband RF PA, does not have to process
    multiple carriers
  • PA Gain is usually fixed so pre-amps may be
    required to drive the PA input.

TX Board
Antenna
RFout 50dBm(100W)
RFin 20dBm_at_ gt800MHz
FromBaseband
PA
DAC
IF-gtRF
DUC
A
50 OhmTypicalInput
3 to 4 gain stages typical
If Gain 30dB,
Pre-Amp
5
Introduction and Impact
  • Linearization techniques allow a PA to be
    operated at higher power with minimal IMD
    increases, thus greater efficiency
  • Recent technological advances have made digital
    pre-distortion the focus of research efforts
  • Crest factor reduction (CFR) further increases
    the efficiency of the PA by reducing the
    peak-to-average ratio (PAR) of the transmitted
    signal

Theoretical Performance of Class AB PA
Pre-Distortion No No Yes Yes
CFR No Moderate Moderate Yes
Tx Power 10W 10W 10W 10W
PAR 12dB 9dB 9dB 6dB
Backoff 15dB 12dB 9dB 6dB
PA Power Rating 320W 160W 80W 40W
Efficency 5 9 18 30
Power Dissipation 120W 101W 45W 7W
6
Origin and History of the Problem
1. Linearization Fundamentals
  • The trade-off between efficiency and linearity is
    the primary concern for PA designers
  • A PA operating at a high percentage of its power
    rating requires external linearization to
    maintain linearity
  • The linearization of the PA reduces back-off,
    thus increasing efficiency

7
Origin and History of the Problem
2. Polynomial Power Amplifier Modeling
  • Accurate representation of the nonlinear effects
    in PAs is achieved using a polynomial expression,
    as follows
  • The coefficients represent the linear gain, and
    the gain constants for the quadratic and cubic
    nonlinearities
  • A system with memory (phase) versus memory
    effects (non-linearities)
  • Envelope and frequency memory effects

8
Origin and History of the Problem
2. Power Amplifier Characterization
  • Two tone test is useful for measuring spectral
    regrowth in a nonlinear and memoryless system

9
Origin and History of the Problem
2. Power Amplifier Characterization
  • Theoretically, only odd-degree nonlinearities
    generate in-band distortion products
  • The simplified polynomial PA model is expressed
    as follows

10
Origin and History of the Problem
2. Power Amplifier Characterization
  • A PA is often characterized by its
    amplitude-amplitude and amplitude-phase transfer
    characteristics
  • The simple polynomial is unable to model AM-PM
    effects
  • Both AM-AM and AM-PM effects are represented by
    the complex baseband model

where
11
Origin and History of the Problem
2. Power Amplifier Characterization
  • A simple case considering only 3rd degree
    nonlinearities in the AM-AM and AM-PM transfer
    characteristics is represented by the following
  • In the linear range, the PA can be characterized
    by the following

and
12
Origin and History of the Problem
2. Power Amplifier Characterization
AM-AM Characteristic
AM-PM Characteristic
13
Origin and History of the Problem
3. Crest-Factor Reduction
  • The DPD optimal performance depends greatly on
    signal characteristics
  • Multi-carrier signals can have a PAR as high as
    13dB increasing the level of back-off to maintain
    acceptable IMD levels
  • The application of CFR allows the PA to operate
    at higher input/output power levels while
    maintaining linearity at the output of the PA
  • Achieved through pulse generation and digital
    clipping

14
Origin and History of the Problem
3. Crest-Factor Reduction
  • Preferred PA bias point for a typical modulated
    signal

15
Origin and History of the Problem
3. Crest-Factor Reduction
  • Preferred PA bias point for a CFR signal

16
Origin and History of the Problem
4. Digital Pre-Distortion
  • Pre-distortion effectively performs a
    mathematical inversion of the Volterra PA model
  • The output of the pre-distortion processor is
    described by the following
  • The PA is linearized when

17
Origin and History of the Problem
4. Digital Pre-Distortion
  • Digital pre-distortion (DPD) has become an
    effective linearization technique due to the
    renewed possibilities offered by DSP
  • Adaptive PD designs use feedback to compensate
    for PA variations
  • Look-up tables are updated to achieve optimal
    pre-distortion by comparing PD input to PA output
  • The PD function is expressed as a complex
    polynomial

where
18
Origin and History of the Problem
4. Digital Pre-Distortion
  • Digital pre-distortion (DPD) requires feedback
    for sample-by-sample adaptation 5 times that of
    the signal bandwidth
  • Multi-carrier systems use signal bandwidths of up
    to 20MHz today, thus the feedback bandwidth must
    be 100MHz to compensate 3rd and 5th order IMD
  • Least-mean-square (LMS) is a popular gradient
    based optimization algorithm that requires
    wideband feedback

19
System Implementation
1. Crest-Factor Reduction and Digital
Pre-Distortion
  • The combination of CFR and digital pre-distortion
    were investigated
  • In this case, linearization was achieved with a
    traditional wideband feedback LMS algorithm
  • The CFR technique used was proposed by Texas
    Instruments using the GC1115 signal pre-processor
  • Four stages ensure that the output PAR is reduced
    to values from 5 to 8dB, as specified by the user
  • Performance results were compared using a Cree
    Microdevices 30W PA operating at 1.96GHz and a
    signal bandwidth of 1.25MHz
  • The PAR of the IS-95 signal was reduced from
    9.6dB to 5dB

20
System Implementation
1. Crest-Factor Reduction and Digital
Pre-Distortion
Complex Canceling Pulse
21
System Implementation
1. Crest-Factor Reduction and Digital
Pre-Distortion
Corrected and uncorrected signal with canceling
peaks and detection threshold
22
System Implementation
1. Crest-Factor Reduction and Digital
Pre-Distortion
Typical Peak Detection and Cancellation through
Pulse Injection
Cancellation Signal
Input Signal
Output Signal
-

23
System Implementation
1. Crest-Factor Reduction and Digital
Pre-Distortion
  • Hardware Implementation of Wideband
    Pre-Distortion

Waveform Generator
Down-Converter
Attenuator
Analog RF
Agilent 4432B
20dB
DUT
Pre-Distorted Input Signal
LO
Tektronics TDS224 Oscilloscope
Analog IF
24
System Implementation
1. Crest-Factor Reduction and Digital
Pre-Distortion
ACPR improvement with respect to output power
25
System Implementation
1. Crest-Factor Reduction and Digital
Pre-Distortion
  • The ACPR measurements were recorded according to
    specifications with a 30kHz marker at and offset
    of 885kHz
  • Results were limited by the performance
    limitations of the test bed

Power and efficiency improvement
26
System Implementation
2. Adaptive Memory Pre-distortion of Power
Amplifiers
  • The term memory effects refer to the
    bandwidth-dependant nonlinear effects often
    present in PAs.
  • These encompass envelope memory effects and
    frequency response memory effects.
  • Envelope memory effects are primarily a result of
    thermal hysteresis and electrical properties
    inherent to PAs.
  • Frequency memory effects are due to the
    variations in the frequency spacing of the
    transmitted signal and are characterized by
    shorter time constants.

27
System Implementation
2. Adaptive Memory Pre-distortion of Power
Amplifiers
  • Memory Polynomial Pre-Distortion Implementation

Where (K7)
And (D2)
28
System Implementation
2. Adaptive Memory Pre-distortion of Power
Amplifiers
  • Simulated Performance of Wideband Pre-Distortion
  • This traditional approach uses and LMS algorithm
    to adapt the PD coefficients on a
    sample-by-sample basis.
  • The memory PA model has D1 (delay) and K5
    (order).

29
System Implementation
2. Adaptive Memory Pre-distortion of Power
Amplifiers
  • Simulated Performance of Wideband Pre-Distortion
  • The memory PA model is characterized by the
    following AM-AM and AM-PM curves

30
System Implementation
2. Adaptive Memory Pre-distortion of Power
Amplifiers
  • Simulated Performance of Wideband Pre-Distortion
  • DPD 0 the LMS algorithm indicates an ACPL
    improvement of -3dB and an ACPH improvement of
    3dB.
  • DPD 1 the LMS algorithm indicates an ACPL
    improvement of -15dB and an ACPH improvement of
    -11dB.

31
System Implementation
2. Adaptive Memory Pre-distortion of Power
Amplifiers
  • Simulated Performance of Wideband Pre-Distortion
  • DPD 2 the LMS algorithm indicates an ACPL
    improvement of -24dB and an ACPH improvement of
    -23dB.
  • DPD 3 the LMS algorithm indicates an ACPL
    improvement of -24dB and an ACPH improvement of
    -20dB.

32
System Implementation
2. Adaptive Memory Pre-distortion of Power
Amplifiers
  • Hardware Implementation of Wideband
    Pre-Distortion
  • TI offers the complete high-performance signal
    chain including DAC5687, CDCM7005, TRF3761,
    ADS5444, and TRF3703.

33
System Implementation
2. Adaptive Memory Pre-distortion of Power
Amplifiers
  • Typical Doherty Amplifier configuration and
    Performance Results

34
System Implementation
2. Adaptive Memory Pre-distortion of Power
Amplifiers
  • Hardware Implementation of Wideband
    Pre-Distortion

35
Conclusions
  • CFR improves DPD performance
  • CFR uses EVM and ACLR to tradeoff for added
    efficiency
  • Depending on modulation schemes the relative
    percentages may vary
  • OFDM modulations are sensitive to EVM
  • 3GPP modulations are sensitive to ACLR

3GPP Relative Tradeoffs
OFDM Relative Tradeoffs
EVM
ACLR
EVM
ACLR
Efficiency
Efficiency
36
Conclusions
  • Relative to a PA that operates normally under
    backoff, DPD adds additional hardware (cost) and
    system complexity to tradeoff for added
    efficiency
  • DPD can effectively remove the negative effects
    of CFR enabling even greater levels of efficiency

DPD Relative Tradeoffs
Cost
Complexity
DPD
EVM
ACLR
CFRDPD
CFRDPD
Efficiency
37
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