open-process algorithm design
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25 November 2013 DSP-P-027 v1.1w
Open-process Algorithm Design
Dr. Desmond Phillips
Blog presentation
A case study: Digital Predistortion
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Normalised FrequencyP
SD
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Linear PA
Non-linear PA
25 November 2013 DSP-P-027 v1.1w2
Standard versus open-process algorithm design
Open-process algorithm design may give you better signal processing
knowledge transfer
“textbook” top-down approach open-process approach
Platform capabilities help shape algorithm choice
25 November 2013 DSP-P-027 v1.1w3
Standard versus open-process algorithm design
Data analysis algorithms are a natural fit for open-process algorithm design
Sample-oriented Digits
Frame-oriented DSP software
Draw observations from data
Evaluate observations
Algorithm
Platform domains
• Lower bandwidth• Numerically sophisticated• Non-deterministic
• High bandwidth• Numerically simple• Deterministic
Input Data Output Information
naturalmapping
25 November 2013 DSP-P-027 v1.1w4
Case Study: Digital Predistortion
Why RF Power Amplifier Linearisation makes a good case study
Power Amp
x(t)
u(t) y(t)
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0.5
1
1.5
V(in)
V(o
ut)
Vin/Vout
Scaled PDF input
Closed-loop data analysis Complex maths at high data bandwidths (e.g. 10’s Msamples/second)
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Normalised Frequency
PS
D (
dB)
Linear PA
Non-linear PA“Spectral regrowth” contaminates adjacent channels
Occasional high amplitude samples are compressed00
25 November 2013 DSP-P-027 v1.1w5
Case Study: Digital Predistortion
Starting Point: the Non-linearity and Linearisation Model
Predistorter PAx(t)u(t)
y(t)
(v)
r(v)
input magnitude v
v
Predistortion with frame-oriented h(v) computation
AM/AM distortion
AM/PM distortion
Magnitude and phase distortion functions
25 November 2013 DSP-P-027 v1.1w6
Case Study: Digital Predistortion
A textbook predistortion algorithm – Indirect Learning Architecture
Predistorter DAC PA
Estimate delay &
compensate
ADC
@+fc
@-fc
x(t) baseband signal
TX signal to antennau(t)
y(t)u(t-t)
Estimate
r-1(v),(v)
Periodic Copy
Compute h(v)
Default “shoehorning” into digits
25 November 2013 DSP-P-027 v1.1w7
Case Study: Digital Predistortion
Alternative algorithm framework from open-process design
Predistorter DAC PA
Cross correlation
Estimate
r(v), (v)
Adaptation
• Fit models
• generate h(v)
• Estimatedelay
ADC
@+fc
@-fc
x(t) baseband signal
TX signal to antenna
u(t)
Elective mapping to digits
Elective mapping to DSPs/w
y(t)
25 November 2013 DSP-P-027 v1.1w8
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Hz
pow
er (
dB)
PSD of input (X) and output (Y)
Y() linearised
Y() unlinearised
X()
Case Study: Digital Predistortion
Simulation Results for x8 oversampled OFDM
Spectral Regrowth Linearised output
Y(w) within ~1dB of PSD of input X(w)
25 November 2013 DSP-P-027 v1.1w9
Conclusions
So what lessons have we learned in this case study?
We have achieved an effective split of functionality in the algorithm framework by thinking which domain does what, best.
– Digits– Maximum Likelihood estimation technique for r(v), (v)– Small footprint in digits (uses 50% of a Spartan XC6SLX4: $10 part)
– DSP software– Adaptation algorithm is software defined– Tuneable for statistically optimal maths and arbitrary PA models.
The open-process approach has given a more desirable, software defined, flexible framework which we can optimise.
25 November 2013 DSP-P-027 v1.1w
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