A Design-to-Test Methodology for SDR and Cognitive...

Copyright © 2010 Agilent Technologies

A Design-to-Test Methodology for SDR and Cognitive Radio

Authors: Greg Jue & Bob Cutler, Agilent Technologies


Agenda

• SDR Waveform Challenges• SDR Waveform Design• SDR Hardware Testing• Cognitive Radio Algorithm Development Challenges• Cognitive Radio Testbed

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Software Defined Radios

Flexibility• Radio can support multiple waveforms: Different formats, different

revisions of a format, backwards compatibility, future-proofing• Combination of DSP/FPGA/GPP C++/HDL• Flexibility increases demands on RF HW performance• HW may be flexible or reconfigurable to more efficiently support

waveforms with significantly different characteristics (e.g. OFDM vs MSK)

Portability• Across single vendors platforms (usually proprietary)• Across multiple vendors platforms (based on standards such as SCA)• Portability of waveform components (e.g. Viterbi decoder)

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Portability and Flexibility

Challenges and opportunities

• RF performance determined by both hardware and software. Performance could change with “bug fix”.

• Hardware platforms may come from different vendors and have different capabilities. Not quite “write-once, run anywhere”.

• Probe points in the signal path are now digital, as well as analog. Need a consistent way to measure.

• Component implementations in C++, HDL, possibly also from different vendors.

• Need to design and test hardware to support waveforms that have yet to be invented.

• Can use test waveforms for development, diagnostics and manufacturing test.

4


Impacts of SDR Technology on Test

RF performance is a combination of baseband processing, radioconfiguration, and RF hardware performance• Hard to isolate root causes of performance problems. Finger pointing

between hardware and software teams and/or suppliers• Need consistent way to quantify “RF Performance” in the both the hardware

and in the soft-bits.• Abstraction layers help with portability, but can introduce performance and

optimization issues (e.g. timing, or optimal hardware configuration for a waveform) as well as organizational issues (hardware and software from different vendors)

Baseband Processing RF

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Example: High TX ACPSeveral Potential Sources of Error

• Insufficient stop band rejection on baseband DSP filter• Poor design• Truncated filter coefficients

• Insufficient numeric resolution (adds digital noise)• Insufficient numeric range (non-linear over/under flow)• Improper timing (PA enable, frequency settling, glitches, etc)• Improperly programmed hardware (excess gain, misconfigured parts)• Distortion in D/A• Poor analog baseband/IF filtering• IF Distortion due to improper levels• Spurious signals• Excessive phase noise• PA Distortion

D/A PAFPGA/DSP

A 2 dB problem is usually a combination of several sub-1dB problems.

Need to accurately characterize performance in both the digital and analog signal paths

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SimulationDesignSignal analysisSpectrum analysisBit-accurateAlgorithmCode generation

Code Generation

Baseband/IF/RF (scope)Signal analysis Spectrum analysisHardware configTiming

RF/IF (VSA)Signal analysisSpectrum analysisPhase noiseLevelsDistortion

D/AFPGA/DSP

Digital (logic analyzer)Signal analysisSpectrum analysisHardware configTimingPacket inspectionRTOS scheduling

A Consistent Way To Measure

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7


Impacts of SDR Technology on TestFuture Proofing

Need a different test strategy when goal is to support future waveforms• Can’t just test supported waveforms, need to test radio configurations

that might be used with future waveforms• When deployed, will Waveform C have adequate RF performance?

(ACP, BER, EVM, spurious, noise figure, etc)

Baseband Processing

FPGA/DSP/GPP

Converters and Flexible RF

Waveform A 2009

Waveform B 2009

Waveform C 2013

How do we ensure that Waveform C will have adequate performance when installed in radios

deployed in 2009?Configure

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SDR Technology Usually Implies Flexible Hardware

TEST APPROACHES

1. Test with real waveforms and their configurations

2. Test broad selection of representative waveforms

3. Test with custom waveforms to exercise different hardware configurations

Signal bandwidthdynamic range

Low phase noise (NB, OFDM)Fast tuning (FHSS, duplex)

Phase coherent (MIMO)

High efficiency (FM)High linearity(OFDM)Pulsed, continuous

Signal power stats(Distortion req’s)Signal BW

Tunable or broadband antennafor frequency coverage

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9


Use Simulation to Design Test Waveforms, Introduce Defects, and Verify Test Coverage

Noise only DC offset Quadrature error

Delay mismatch

Distortion

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Agenda


11


Design SDR RF Using Various Types of Waveform Formats

Use waveform sources to design SDR RF

Waveform Sources• HDL code• FPGA hardware • Simulation models• Algorithm code

Waveformsignal source

Simulated RF transmitter design

12


Example 1: Use HDL-Based WiMAX™ Waveform to Design SDR RF Transmitter

EVM = 8.4%

Simulated SDR transmitter output

Simulated RF transmitter designVSA

measurement

Waveform sources• HDL code• FPGA hardware • Simulation models• Algorithm code

“Mobile WiMAXtm” is a registeredtrademark of the WiMAX Forum.

13


EVM = 9.1%



measurement

Waveform sources• HDL code• FPGA hardware• Simulation models• Algorithm code

Example 2a: Use FPGA-Based Legacy Waveform toDesign SDR RF Transmitter

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EVM=10.5%

Reconfigure legacy FPGA waveform for a new

waveform (LTE)


measurement


Example 2b: Re-Configure FPGA-Based Waveform toEvaluate SDR RF Transmitter Design Interoperability


15


Example 2c: Probing an FPGA Waveform with Dynamic Probe

Simulated RF transmitter design


Preliminary work-in-progress16


Simulated RF receiver design

Waveform simulationreceiver

Waveform simulation

source

Pre-configured algorithm models (customizable) Select ADC model…


Example 3a: Use Simulation-Based WiMAX Waveform to Design SDR RF Receiver

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QPSK BER vs. ADC Jitter vs. EbNo

Red: 4% ADC JitterBlue: 6% ADC JitterGreen: 8% ADC Jitter

16 QAM BER vs. ADC Jitter vs. EbNo 64 QAM BER vs. ADC Jitter vs. EbNo

Example 3a Results: WiMAX BER vs. ADC Jitter

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New waveform simulationreceiver New waveform

simulationsource

Replace WiMAX waveform source & receiver with LTE

New BER results

Example 3b: Replace Waveform to Evaluate SDR Receiver Design Interoperability

19



Customize OFDMA algorithms

Example 4: Use Algorithm Code Waveforms

20


*Please note: this next section of the presentation contains “Preliminary” product information that is part of new product development (next 3 slides)

21


SCA Waveform Rapid Prototyping Concept

Waveform Components/

BlocksRF Tx RF Channel/ RF

Interferers/Jammers RF RxWaveform

Components/Blocks

Physical-layer environment for waveform development/verification

SCA compliant environment For component design,

implementation, and deploymentFunctional Componentwrapper

Deployablecomponent

ExportImport “OE in the loop”Component

Model

22

Preliminary


Example 5: SCA Waveform DesignExport C++ and XML

PHY

Link

23

Preliminary


Example 5: Verify End-to-End System with OE In the Simulation Loop

QPSK Transmitter(OE-in-the-loop)

RF Channel

BER Sink

ADI ADC

RF Transmitter RF Receiver

PA Output Receiver Digital Output

QPSK Receiver(OE-in-the-loop)

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Preliminary


Agenda


25


SDR Hardware Testing

SDR testing challenges:• Custom/proprietary waveforms not supported by COTS test

equipment• Flexible SDR test platforms are needed for today’s and tomorrow’s

waveforms• Different tools used between design and test- makes it difficult to

debug issues • Solution- Combine the flexibility of simulation with test equipment

for flexible SDR testing

26


16822A Logic Analyzer with Agilent SystemVue*

14 Bit A/D board DUT

* Note: SystemVue does not ship with logic analyzer

• Test waveform coding/decoding SW-defined• Customizable algorithms• Customizable test waveforms

Adding Flexibility to SDR Testing with Simulation

27


OFDMA BER Hardware Test Results

28


Simulate an SDR Receiver with a Hardware Front End (N6841 RF sensor)

Wideband RF sensor

HW DUT test signal


VSAmeasurement

Simulated SDR receiver output

29


Agenda


30


Cognitive Radio

• Many definitions of CR.• A radio that is aware of its environment and adjusts its behavior accordingly.

• Key application for CR is Dynamic Spectrum Access(DSA)

• Radio adjusts frequency, power, modulation based on sensed spectrum, location, policy and databases

• Complimentary to SDR in this application

31


Filling the Whitespace

Goal: Increase spectrum utilization without causing interference

32


CR Design and Measurement Considerations

• Interference (actual, or potential for)

• Radio system performance (capacity, link establishment and reliability)

• Radio physical layer performance (e.g. adjacent channel power)

• Environment sensing performance (spectrum sensing, location sensing)

• Policy performance (does the policy over, or under protect)

• Radio environment (channel, noise, occupancy)

33


Challenges of Spectrum Sensing

Performance of various spectrum sensing algorithms– False positives, false negatives– Response to real-world signal environment (dynamic, many

signals)– Radio design

• Spurious• Amplitude accuracy• Intermod distortion• Sensitivity• Selectivity• Frequency accuracy

– Speed/complexity/cost tradeoffs

34


CR Development Needs

• Need to characterize, capture, and replicate real-world spectral environments.

• Needs to be done over time, frequency and location.• Need to use captured environments to evaluate CR algorithms and

radio link performance. • Need to evaluate performance using non-ideal radios.

• Need a flexible and comprehensive CR R&D Testbed!

35


Agenda


36


Cognitive Radio R&D Testbed

37


CR Algorithm Development and Testing Environment

38


Mobile WiMAX Case Study

39


Step 1: Capture Signal and Bring into SystemVue

Captured CR environment

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Step 2: Whitespace Math Algorithms Determine Valid Whitespace

Frequency Rules Policy

Valid whitespace determined within

the policy

Rising/falling edgesdetected to determine

whitespace

41


Debugging Whitespace Algorithms

Add/remove breakpointSingle-step through code

Code variable values aredisplayed as code is

single-stepped

42


Step 3: Whitespace Math Algorithms Determine Valid Whitespace

WiMAX spectrum (scaled and centered

in the valid whitespace)

43


Analyze Detect-and-Avoid Interferer Scenarios

Sweep narrowbandinterferer vs. frequency to evaluate impact on OFDMA BER

Narrowbandinterferer

44


Sensed spectrum

Step 4: Identify Detected Signals in Simulation or with Test Equipment

45


Remotely located N6841A RF sensor

www.agilent.com/find/eesof-cognitive-whitepaper

Video Demo with SystemVue + N6841A N6841A is Remotely Located Across Washington State

46


New Whitepaper Available: www.agilent.com/find/eesof-cognitive-whitepaper

47


Summary

• Use waveforms sources in various formats (HDL, FPGA hardware,simulation models, math algorithms) to design SDR transmitters andreceiver and evaluate interoperability

• Use improved SCA waveform flow for SDR waveform design and test

• Seamless integration between design and test capability • creates flexible SDR testing platform • enables R&D engineers to develop and test algorithms and hardware

with real field signals

• Evaluate Cognitive Radio link performance, perform ‘what-if’ detect-and-avoid interference scenarios

Explore a Cognitive Radio simulation example in the SystemVue 2009.08 example set – request a free evaluation at:

www.agilent.com/find/eesof-systemvue-latest-downloadsOr, contact your local Agilent representative

48

http://www.agilent.com/find/eesof-systemvue-latest-downloads�


Additional Resources

Product Web sites:

SystemVue http://www.agilent.com/find/systemvue

RF sensors http://www.agilent.com/find/rfsensor

Whitepapers and application notes:

Cognitive Radio Algorithm Development and Testing:http://www.agilent.com/find/eesof-cognitive-whitepaper

Software Defined Radio Measurement Solutions:http://cp.literature.agilent.com/litweb/pdf/5990-4146EN.pdf

Solutions for Addressing SDR Design and Measurement Challengeshttp://www.agilent.com/find/sdrhttp://www.agilent.com/find/powerofx

Videos:

Web video of CR Testbed discussed in this paper:http://www.agilent.com/find/eesof-cognitive-whitepaper

49

http://www.agilent.com/find/systemvue�

http://www.agilent.com/find/rfsensor�

http://www.agilent.com/find/eesof-cognitive-whitepaper�

http://cp.literature.agilent.com/litweb/pdf/5990-4146EN.pdf�

http://www.agilent.com/find/sdr�

http://www.agilent.com/find/powerofx�

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Thank You!

50


For more information aboutAgilent EEsof EDA, visit:

www.agilent.com/find/eesof

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Product specifications and descriptions in this document subject to change without notice.

© Agilent Technologies, Inc. 2010Printed in USA, October 29, 20105990-6694EN

www.agilent.comwww.agilent.com/find/eesof-systemvue

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