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“RF and Microwave System Design for A/D and Commercial Wireless applications”
Agilent EEsof EDA - European Microwave Week 2011 Workshop Series
Presenters: Stephen Slater, EEsof Application Engineer Jake Sanderson, MPO Application Engineer
Group/Presentation Title
Month ##, 200X Page 2
• A Systems Modeling Approach • Communications Applications • Aerospace Defense Applications
• System Demonstration • Digital PreDistortion Overview • Wideband DPD Demonstration
Agenda
PHY Architecture Research Analysis
Partitioning Verification
Instrument Links
MIMO/Channel Fading
Jamming Noise
Interference Arrays/Steering
A Systems Modeling Approach Focused on improving system-level design for Defense & Communications
Baseband DSP Modeling Algorithms
Code-Generation Fixed Point/HDL
Verification
RF System Architecture
Behavioral/Noise X-parameters
Links from ADS/GG
PHY Reference IP Wireless Standards
Interoperability Virtual H/W
Coded Test Vectors EDA/Test integration
Target Applications
AEROSPACE / DEFENSE EMERGING COMMS PHY
SDR MILCOM
SATCOM EW ELINT
BROADCAST
3G/4G MOBILITY
NETWORKING
CONNECTIVITY
RADAR
• Superior RF-Baseband architectures • Accelerated real-world design maturity • Lower verification costs
GIGABIT SerDes
Superior BB RF co-design • Allows aggressive Baseband/RF partitioning • Reduces design margins • Lowers risk where BB+RF matters: - wide bandwidth - high linearity/dynamic range - high data throughput - high spectral efficiency/occupancy - high PHY complexity - dynamic behaviors, and quasi-MAC interaction
Value of System Modeling RF-DSP cross-verification bridges the “A/D Converter Gap”
Typical Design Organization
ARCHITECTURE
IMPLEMENTATION
Unified architecture, verification for Layer 1 Comms Augments general purpose tools, or, stands on its own
PHY system integration and verification
Cross-domain PHY modeling framework, for Model-Based Design
Complete a working PHY using combinations of Software, RF/BB Hardware, Simulation, and Measurements
Baseband Algorithms Dataflow Simulation
RF Sys Architecture RF Simulators
Agilent SystemVue
PHY IP
TEST RF Hardware Flows RFIC / MMIC
Hardware SiP / Board Hardware
Baseband Hardware Flows
GPP/ARM Software
DSP/ASSP Software
FPGA/ASIC/SoC Hardware
SystemVue improves top-down PHY System Design with 4 key strengths
Easily assemble Virtual PHYs
Quickly move Ideas to proven, real-world Hardware WiMAX
DVB-S2 ZigBee OFDM
DPD RADAR MIMO Channel mmWave WPAN
HARDWARE & MEASUREMENT CONNECTIVITY
INDUSTRY-LEADING REFERENCE IP
and APPS
POLYMORPHIC BASEBAND
ALGORITHMS & IP
ACCURATE RF & CHANNEL
EFFECTS
.bit Files
FPGA Synthesis
Handwritten HDL
Custom IP
Integrated, tops-down Comms ESL flow Cross-domain model-based design: RF, Comms, and C++/HDL
FPGA Target
REAL HARDWARE
HDL Simulator(s)
SIMULATED H/W
Dataflow Simulation
.m/C++ ALGORITHM
Algorithms C++, .m
Target-neutral HDL Generation
System design RF Architecture
Baseband design PHY Reference
MEASUREMENT, ANALYSIS
VSA software FlexDCA software
DIGITAL BITS, or MODULATED CARRIERS
MXG / ESG
Infiniium Scope
Logic Analyzer
MXA / PXA
Wideband arbs RF sensor
Communications Applications – Partitioning Design Requirements
Phase Noise ADC Jitter
RF Transmitter/ PA Nonlinarities
Baseband Fixed-Point Mixed-Signal
Receiver
Tx Rx Coding Algorithms
D/A
Bits In Decoding Algorithms
Bits Out
RF Channel A/D
Coding/ Decoding
Algorithms
If we take LTE as an example with high performance targets, every part of the transmit and receive chain becomes critical to the link budget
So how to decide the optimum balance, without over-designing?
How are design requirements impacted going from QPSK to 16QAM to 64QAM?
Coding/ Decoding
Algorithms Algorithm Test Vectors for FPGA Development
Baseband Affects RF? Baseband Fixed-Point
Transmitter Design System-Level Trade-Offs
Transmitter Design
RF Transmitter/ PA Nonlinarities
Evaluating BER Performance vs Swept Eb/No and Phase Noise
Specify Phase Noise (e.g. -80 dBc/Hz @ 10kHz offset) Phase Noise
ADC Jitter
Mixed-Signal Receiver
Simulation Results for QPSK, 16QAM, 64QAM vs. Swept Phase Noise at 10 kHz Frequency Offset
-60 dBc/Hz
-70 dBc/Hz
-80 dBc/Hz
RF System Architecture – “Spectrasys” continuous spectrum simulation
Full continuous spectrum at every node (unique RF simulator)
Track origin and propagation of spurs, noise, mismatch, leakage paths
Easily plot Budget & Spectral info
Create and refine RF System Architectures, then use them in System-level Dataflow
A base-station user says . . .“After briefly using SPECTRASYS on a 'must work right the first time' RF design, I identified several issues that were undetected in our spreadsheets and current simulation tools. I'm absolutely positive that it has saved us at least one board spin! ”
RFLINK – “Virtualizes the RF” to enable concurrency
Drag & Drop Dataflow modeling “on the fly”
Automated model-based link captures RF effects: - power/frequency-dependence - broadband noise spectral densities - spectral inversion from up/downconversion
Fast, convenient, enables BB-RF concurrent design Enjoy superior RF results with less detailed
RF knowledge, and less RF flow integration
Using X-Parameters in dataflow with “RF Link”
X-parameter physical effects – contribute to the overall RF System performance – therefore affect link-level Dataflow performance also
Baseband and System-level users – can also enjoy convenient access to RF implementation accuracy,
without understanding the RF design, or learning/maintain the RF tools
LTE-Advanced baseband verification library Industry’s first design support for 3GPP Release 10
Carrier Aggregation: Enhanced Multi-Antenna Technologies:
A/D Applications - Radar Model Library New features for digital array, beamforming
Tx Waveform Tx / Rx Components Measurement
Pulse Generator • LFM • NLFM • BarkerCode • FrankCode • ZCCode Coherent Signal Generator for Multiple Channel (future)
• Tx Front-end • Rx Front-end • DUC • DDC • DAC • ADC • PA • Filter • DDS? • LNA?
Environment Radar Signal Processing
• Detection Prob. • False alarm rate
• Target • RCS • Clutter • Jammer • Interference
• Digital Pulse Compression (PC) • Moving Target Indication (MTI) • Moving Target Detection (MTD) • Pulse Doppler Processing (PD) • Constant False Alarm Rate (CFAR)
• Digital Beam-forming (future) • Space-Time Adaptive Processing (STAP) (future)
Antenna (future)
• Antenna Models • T/R Antenna Array • Antenna Propagation
SystemVue “integrated test solutions for A/D” Continue model-based verification from S/W into the real world
RF Signal Analyzers Logic Analyzers, Oscilloscopes VSA software
OPTIONAL: UPLOAD BACK TO SystemVue TO TEST YOUR SOFTWARE RECEIVER IP
Standards Based IP Reference Models
Fading, noise, and Interference
BB Pattern Generator BB Arb. Waveform Gen Agilent wideband Arb’s RF Signal Generator
DOWNLOAD FROM
SystemVue SystemVue Radar Library
RF Transmitter RF Receiver
BB DSP/FPGA
MEASURE HARDWARE DEVICE UNDER TEST
STEP 1
STEP 2
Perform earlier physical layer Fcn verification LTE FDD UL Throughput Test (TS 36.141), or BER/BLER
Filter X
~
Filter A/D 1 2 3 4
DU Gain DPD Filter X
~
A/D
RU DU
C P R I
Signal Generator
Signal Analyzer
SystemVue – Generates signal, then closes the loop
VSA 89600 waveform recording SystemVue – LTE decode
Customer Hardware eNodeB receiver
STEP 1
STEP 2
SystemVue closed a loop to help measure LTE throughput
APP NOTE 5990-6202EN
MIMO and Multi-channel/Beamforming apps Using SystemVue to virtualize multiple signals, RF channels
1,2,4,8 MIMO
Additional support for hardware verification Leverage SystemVue for apps that “fall between” other products
FILL HOLES
OFDM, MIMO LTE-Advanced
WNW, Defense
Jamming, Interfere Clutter, Targets RF, Phase Noise Cognitive environments
Throughput Coded BER
DPD
MULTI-BOX COORDINATION Digital vs. RF interfaces
Missing test coverage Missing user hardware
NON-STD WAVEFORMS
FADING, IMPAIRMENTS
How SystemVue connects to instrumentation
MATLAB .m modeling
Signal Studio
(licensed)
VSA visualization, connectivity
TCP/IP SCPI
FlexDCA visualization
(free with SV)
MATLAB™ scripting plotting
Agilent I/O Lib Connectivity
(free with SV)
PSA/PXA/MXA Infiniuum/DCA PXI/Modular Simulation
Any test H/W Customer equipment Customer Virtual Plat Simulators and Apps
File I/O
ESG MXG PSG Arbs
Modeling Interfaces Scripting Reference IP
PNA-X X-parameters
Group/Presentation Title
Month ##, 200X Page 25
• A Systems Modeling Approach • Communications Applications • Aerospace Defense Applications
• System Demonstration • Digital PreDistortion Overview • Wideband DPD Demonstration
Agenda
Group/Presentation Title
Month ##, 200X Page 26
• A Systems Modeling Approach • Communications Applications • Aerospace Defense Applications
• System Demonstration • Digital PreDistortion Overview • Wideband DPD Demonstration
Agenda
Conflicting requirements
Problem Statement
27
How to handle signals with high Crest Factor, while driving the PA to operate with high PAE, while also having low signal distortion?
High DC-RF Efficiency
High Crest Factor
High Spectral
Efficiency
Increase Drive levels
Causes high distortion
levels
“Back off” the drive
levels
Solution Approach
28
High DC-RF Efficiency High
Crest Factor
High Spectral
Efficiency
Increase Drive levels
Causes high distortion
levels
Higher Throughput
rates for subscribers
CFR
DPD
CFR
DPD
29
Psat
Pin
LINEAR GAIN
INPUT POWER
OUTPUT POWER
Pdesired
Pactual
Pin needed to achieve Pdesired
PA, WITH GAIN COMPRESSION
Digital Pre-distortion principles – compressing PA
30
Digital Pre-distortion principles – pre-expansion
Maximum correctable power
Psat
LINEAR GAIN
INPUT POWER
OUTPUT POWER
LINEAR REGION
DPD REGION
PA, WITH GAIN COMPRESSION
DPD GAIN EXPANSION
+
31
Maximum correctable power
Psat
INPUT POWER
OUTPUT POWER
LINEAR REGION
DPD REGION
LINEARIZED DPD + PA
Digital Pre-distortion principles – linearized result
PA, WITH GAIN COMPRESSION
DPD GAIN EXPANSION
+ =
Linear Operation with time-varying envelope
32
Psat
LINEAR GAIN
INPUT POWER
OUTPUT POWER
Peak-to-Avg Power Ratio
COMPLEX ENVELOPE
time
Peak Average
Nonlinear Operation – peaks are compressed
33
Psat
LINEAR GAIN
INPUT POWER
OUTPUT POWER
(compressed peaks)
CCDF (LTE)
+19 dBm output, for a Handset PA LTE signal, PA operating at ~1.5 dB overall gain compression
DPD Pre-Expansion – peaks are exaggerated
35
Psat
LINEAR GAIN
INPUT POWER
OUTPUT POWER
Further Improvements: • Compensate for artificially higher avg. signal power • Condition signal w/Crest Factor Reduction (CFR)
(expanded peaks)
DPD Net Result: Linear gain of complex-valued RF carrier envelope over a specific range of power levels
36
LINEAR
INPUT POWER
OUTPUT POWER
DPD pre-expanded peaks
INPUT POWER
PA compresses peaks LINEAR
Baseband Digital Pre-Distortion
RF Power Amplification
AM-AM Effects (Change in Gain vs. Power level)
Pre-Distorter AM-to-AM
DPD + PA AM-to-AM
Linearized PA
Power Amp AM-to-AM
Definitions • AM-AM : Change in Gain vs. Power level, compared to small-signal (dB(S21)) • AM-PM : Change in Transmission Phase, compared to small-signal (phase(S21)) • CCDF: Percentage of time a particular amplitude level spends above avg power
Additional issues: Memory Effects Output is dependent on previous history; “path dependence”
PA with memory AM-to-AM
PA without memory AM-to-AM
Output waveform has an instantaneous 1:1 correspondence in time with input waveform
Output waveform depends on previous values
What does a DPD look like? (Volterra Model)
39
∑=
=K
kk nznz
1)()( ∑ ∑ ∏
= = =
−=Q
m
Q
m
k
llkkk
k
mnymmhnz0 0 1
11
)(),,()(
∑∑∑= ==
+−−+−+=Q
m
Q
m
Q
mmnymnymmhmnymhhnz
0 021212
01110
1 21
)()(),()()()(
Volterra series pre-distorter can be described by
where
Which is a 2-dimensional summation of power series & past time envelope responses
A full Volterra produces a huge computational load. People usually simplify it into • Wiener model • Hammerstein model • Wiener-Hammerstein model • Memory polynomial model
DPD principles – Memory Polynomial Model
If only diagonal terms are kept, Volterra reduces to “Memory polynomial” model.
Agilent uses an indirect learning algorithm to extract MP coefficients.
As of SystemVue 2011.10, you can now add your own model, extraction algorithm, and even create your own GUI.
40
L. Ding, G. T. Zhou, D. R. Morgan, Z. Ma, J. S. Kenney, J. Kim, and C. R. Giardina, “Memory polynomial predistorter based on the indirect learning architecture,” in Proc. of GLOBECOM, Taipei, Taiwan, 2002, vol. 1, pp. 967–971.
∑∑= =
−−−=K
k
Q
q
kkq qnyqnyanz
1 0
1)()()(
Where • K is Nonlinearity order • Q is Memory length
DPD challenges for 4G/wideband systems
• LTE-Advanced (100MHz) and 802.11ac (160MHz) are physically 5x-8x wider than previous generation
• Oversampling increases this bandwidth an additional 3x-5x
• Drives wider ADC/DAC, data rates, test equipment, & more
• Requires powerful embedded processors : DSP/FPGA/ASIC
Wider Bandwidth
Higher Crest Factor
Rapidly changing environment
Oversampling increases the Measurement BW
1x
3x-5x
oversampling
oversampling
Measures: In-band EVM, Throughput
Measures: Out-of-band Spectral Masks
Most Effective DPD Region
DPD challenges for 4G/wideband systems
• Carrier aggregation increases PAPR (drives Efficiency down)
• Highly-configurable signals (time-varying RBs) can lead to worst-case RF scenarios
• People apply Crest Factor Reduction differently…. ….how to estimate the effect of CFR on your PA if someone else is doing the DSP?
Wider Bandwidth
Higher Crest Factor
Rapidly changing environment
CCDF
The Effect of Carrier Aggregation on PAPR
Carrier Agg.
Scenario
Link Type
Configuration PAPR of single CC, before aggregation
PAPR with CCs, after aggregation
Scenario 1 FDD DL 4x20 MHz CCs 8.45 dB 9.98 dB
Scenario 2 TDD DL 5x20 MHz CCs 9.17 dB 11.71 dB
Scenario 4 FDD DL 2x20+2x20MHz 8.38 dB 9.58 dB
FDD UL 20 + 20MHz 5.79 dB 6.86 dB
CA Scenario 1 FDD DL
CA Scenario 2 TDD DL
CA Scenario 4 FDD DL CA Scenario 4 FDD UL
DPD challenges for 4G/wideband systems
• LTE-Advanced, 802.11ac, and other Standards still changing
• IP issues: interoperability of signals, algorithms, channels, coded performance
• Closed DPD IP (no control) • Availability of commercial DPD
solutions • Ecosystem & vendor
re-alignments • BB/RF hardware platform
neutrality for local spectral variations, vendors, standards
Wider Bandwidth
Higher Crest Factor
Rapidly changing environment
Wideband modeling platform
N5182A MXG, or E8267D PSG (as external modulator)
W1461 SystemVue W1716 DPD 89600B VSA
M9330A AWG
M9392A PXI VSA
Device Under Test
Baseband I,Q
How is this wideband modeling platform used?
WIDEBAND MODELING PLATFORM
WIDEBAND RF SOURCE
WIDEBAND RF ANALYZER
.m, C++, VHDL
Test Vectors
Standards reference
DPD, CFR
Early R&D Scenarios
Architectures Algorithms
System-level Validation Vendor Qualification Component Design
Deployment Scenarios
COMMS PHY ….. BASEBAND
IF/RF UPCONVERSION DPD
COMMS PHY BASEBAND
IF/RF UPCONVERSION
FPGA / DSP REALIZATION
Wireless SoC DPD
Wideband modeling – software
Flexible modeling environment, integrates .m, C++, VHDL, along with instrument drivers, simulators, scripting
DPD modeling & extraction algorithms
Instrument control
Wireless Standards libraries, for test vector generation and system-level tests
Connection to VSA software, RF EDA design flows, MATLAB, and other tools
W1461 SystemVue W1716 DPD 89600B VSA
Wideband platform – PXI modular instruments
Stimulus – User-defined (or locally generated) test vectors – Wideband, calibrated AWG – RF/MW signal generator (modulate & upconvert) – Driver pre-amp (optional)
Response – RF/MW downconverter, attenuator, signal conditioning – Wideband baseband digitizer
Integration pieces – DC bias source, cables, connectors, PA output
attenuator, etc.
M9330A AWG
M9392A PXI VSA
N5182A MXG, or E8267D PSG (as external modulator)
Wideband platform Demonstration –
Wideband platform – SystemVue with modular PXI instruments (bandwidth ~250MHz)
~10 dB improvement
in spectral leakage
(1st iteration)
1. Instrument setup to capture PA input signal
2. Instrument setup to capture PA output signal
Wideband platform
External Trigger
M9330A AWG
MXG as external modulator M9392A PXI VSA
M9392A PXI VSA
External Trigger
Attenuator
M9330A AWG
MXG as external modulator
SystemVue DPD Hardware Flow for LTE/LTE-A
The download power and length of the waveform can also be set.
53
Step 1. Create DPD stimulus waveform • LTE parameters such as bandwidth, Resource Block allocation and others
can be set. • Switch LTE or LTE-Advanced waveform
Connect the MXG/AWG directly to the PXA/M9392A and click the “Capture Waveform” button. The captured signal is the input of the PA. Connect the MXG to the PA, connect the PA to the PXA/M9392A, and click the “Capture Waveform” button. The captured signal is the output of the PA DUT. The measured I/Q files are stored and used in following steps.
54
Step 2. Capture PA response • SystemVue interfaces directly to the MXG or M9330A AWG (source) and PXA
or M9392A(analyzer). • Instrument parameters such as number of signal, trace assignment and file
name can be set.
SystemVue DPD Hardware Flow for LTE/LTE-A
DPD AM-to-AM Characteristic
55
SystemVue DPD Hardware Flow for LTE/LTE-A
Step 3. DPD Model Extraction • DPD model parameters such as number
of training samples, memory order and nonlinear order can be set.
PA AM-to-AM Characteristic
56
SystemVue DPD Hardware Flow for LTE/LTE-A
Step 3. DPD Model Extraction (Custom IP) • Provide UI to allow customers to export their
own Matlab code of DPD algorithm (IP) into MathLang to verify their DPD algorithm performance.
Custom DPD Model Extraction
Custom Digital Pre-distorter
57
SystemVue DPD Hardware Flow for LTE/LTE-A Step 4. Capture DPD+PA Response • The signal is predistorted by the DPD model
and downloaded into the MXG or M9330A AWG. DPD+PA output (blue) and original raw signal (red) is displayed
Set the RF power DPD+PA AM-to-AM Characteristic
SystemVue DPD Hardware Flow for LTE/LTE-A
Step 5. Verify DPD+PA response • LTE performance for the DPD model used with the PA hardware is verified.
Spectrum, EVM and ACLR are calculated and plotted automatically
58
Simulation vs. Measurement DPD Extraction
External Trigger
Attenuator N5182 MXG
or E8257D PSG as external modulator M9330A AWG if > 100 MHz
89600 VSA
M9392A PXI VSA (>140MHz) or N9030A PXA (<140 MHz)
I,Q RF
RF DUT
SIMULATION-BASED DPD (predictive)
• ADS & GoldenGate Circuits as simulated RF DUTs - Complex loading, memory FX, dynamic behaviors • NVNA X-parameter measurement model, - Great for smaller solid-state devices
X-parameters
RF DUT N5241,2 PNA-X
MEASUREMENT-BASED DPD
CO-SIM, MODELS
CO-SIM, MODELS
MODEL
ADS
GG
Simulation-based, predictive DPD
ADS circuit-level PA
(circuit envelope simulation)
ADS Ptolemy (circuit-system co-
simulation)
SystemVue STIMULUS
SystemVue RESPONSE
CO-SIM
• Full, nonlinear RF • Time-varying behaviors
& memory effects • Envelope Tracking • Complex loadings • No H/W limitations
CO-SIM
Applications: Early assessment, early validation, cross-domain troubleshooting
Conclusion
New bandwidth and linearity requirements are driving 4G designers to spec DPD earlier in their system designs
The velocity of the industry is pushing DPD activity in-house, where designers are taking a more active role
The integration of an open Comms EDA environment with versatile wideband instruments enables
– Flexibility for modeling, realization, validation, and troubleshooting – Higher performance – Integration with the baseband DSP you are already doing
Further information
About Wideband DPD – Watch a demo:
http://www.youtube.com/watch?v=bocF6P74T9E – Read an app note:
http://cp.literature.agilent.com/litweb/pdf/5990-8883EN.pdf
About Agilent Products – http://www.agilent.com/find/eesof-systemvue – http://www.agilent.com/find/modular
Contact
– Stephen Slater ([email protected])
– Jake Sanderson ( [email protected])
Q&A
1. Lei Ding, Zhou G.T., Morgan D.R., Zhengxiang Ma, Kenney J.S., Jaehyeong Kim, Giardina C.R., “A robust digital baseband predistorter constructed using memory polynomials”, Communications, IEEE Transactions on, Jan. 2004, Volume: 52, Issue:1, page 159-165.
2. Lei Ding, “Digital Predistortion of Power Amplifiers for Wireless Applications”, PhD Thesis, March 2004. 3. Roland Sperlich, “Adaptive Power Amplifier Linearization by Digital Pre-Distortion with Narrowband
Feedback using Genetic Algorithms”, PhD Thesis, 2005. 4. Helaoui, M. Boumaiza, S. Ghazel, A. Ghannouchi, F.M., “Power and efficiency enhancement of 3G
multicarrier amplifiers using digital signal processing with experimental validation”, Microwave Theory and Techniques, IEEE Transactions on, June 2006, Volume: 54, Issue: 4, Part 1, page 1396-1404.
5. H. A.Suraweera, K. R. Panta, M. Feramez and J. Armstrong, “OFDM peak-to-average power reduction scheme with spectral masking,” Proc. Symp. on Communication Systems, Networks and Digital Signal Processing, pp.164-167, July 2004.
6. Zhao, Chunming; Baxley, Robert J.; Zhou, G. Tong; Boppana, Deepak; Kenney, J. Stevenson, “Constrained Clipping for Crest Factor Reduction in Multiple-user OFDM”, Radio and Wireless Symposium, 2007 IEEE Volume , Issue , 9-11 Jan. 2007 Page(s):341- 344.
7. Olli Vaananen, “Digital Modulators with Crest Factor Reduction Techniques”, PhD Thesis, 2006 8. Boumaiza, et a, “On the RF/DSP Design for Efficiency of OFDM Transmitters” , IEEE Transactions on
Microwave Theory and Techniques, Vol. 53, No. 7, July 2005, pp 2355-2361. 9. Boumaiza, Slim, “Advanced Memory Polynomial Linearization Techniques,” IMS2009 Workshop WMC
(Boston, MA), June 2009.
Selected DPD References
Recent DPD resources from Agilent
App Notes http://cp.literature.agilent.com/litweb/pdf/5990-8883EN.pdf (Wideband DPD)
http://cp.literature.agilent.com/litweb/pdf/5990-7818EN.pdf (3G/4G)
http://cp.literature.agilent.com/litweb/pdf/5990-6742EN.pdf
http://cp.literature.agilent.com/litweb/pdf/5990-6534EN.pdf (algorithms used)
Demonstration Videos http://www.youtube.com/watch?v=bocF6P74T9E (Wideband DPD)
Previous Webcasts “4G For Everyone: Extended RF Performance with DPD” (June 2010) http://www.home.agilent.com/agilent/eventDetail.jspx?cc=US&lc=eng&ckey=1842093&nid=-11143.0.00&id=1842093