Dr. Charles Baylis Faculty Candidate baylis@engf April 11, 2008

1. Improving the RF Active Circuit Design Cycle Through Innovations in Electrothermal Modeling, Characterization, and Design Techniques Dr. Charles BaylisFaculty Candidatebaylis@eng.usf.eduApril 11, 2008

2. Overview • USF RACAM Research Group • The RF Active Circuit Design Cycle • Research Strategy/Overview • Nonlinear Modeling of Thermal and Trapping Effects in GaN HEMTs • Radar Power Amplifier Combining Techniques for Sidelobe Reduction • Prediction of Phase Noise in Amplifiers and Frequency Multipliers • Development of Microwave Measurement Techniques for Cell Cultures

3. University of South Florida

4. RACAM at USF • 4 graduate students, 2 undergraduate students

5. RF Active Circuit Design Cycle Design Measurements Simulation Models Fabrication Testing SUCCESS!!! Good models can eliminate this path.

6. Strategy for Obtaining Funds • Obtain initial grass-roots funding from industry contacts. • From this foundation, apply for agency funding.

7. Research Overview • Nonlinear Modeling for Power Amplifier Design (Modelithics) $25,000 + $25,000 State Program Match = $50,000 • Prediction of Phase Noise in Amplifiers and Frequency Multipliers (Trak Microwave) $12,000 + $6,000 State Program Match = $18,000 • Investigation of Combining Techniques for Reduced Sidelobes in Radar Power Amplifiers NRL Proposal – March 2008, $170,000 for 2 years

8. Research Overview • Accurate Bio-Impedance Measurements NSF Proposal - February 2008, $361,381 for 3 years • Research on a Wireless System for Transportation Applications Proposal to Sunovia Energy Systems, February 2008, 3 years • Development of Model Scoring Metrics for RF Circuit Design Proposal to Raytheon RF Components (Andover, Massachusetts), $49,500 for 1 year

9. Electrothermal FET Modeling • Nonlinear RF CAD Models are extracted from measurements of Field-Effect Transistors (FETs): • Current-Voltage (IV) • S-Parameters • Load Pull • Pulsed IV measurements allow thermal and trap effects to be accurately modeled.

10. IV Curves • The IV curves give the boundaries for the large-signal performance of the FET: Maximum Current Drain-gate breakdown ID Knee Voltage Load line for signal swing VDS

11. Model Equation Fitting to IV Blue Dots = Measured Red Lines = Simulated

12. Pulsed IV Measurements • Static measurements can be inaccurate for RF models. • The cause: Slow Thermal and Trapping Processes • Solutions: Pulsed IV and Measurements • GaN HEMT Static (Dark Lines) and Pulsed IV (Light Lines)

13. Pulsed IV Measurement • Measurements are performed during brief (~0.2 μs) excursions from a quiescent bias. • The pulses are usually separated by at least 1 ms. • Thermal and trap conditions during the measurement are those of the quiescent bias, as in high-frequency operation.

14. S G Surface Traps D Electron Flow Substrate Traps Trapping Effects • Trapping Effects in MESFETs (Charbonninud et. al): • Substrate Traps • Surface Traps • Electron Capture  Fast Process • Electron Emission  Slow Process

15. Summary of Trap Processes ID Surface Hole Capture (Slow) SLOW PROCESSES FAST PROCESSES  Substrate Electron Emission (Slow) Surface Hole Capture (Slow) Substrate Electron Capture (Fast) Surface Hole Emission (Fast) Q Surface Hole Emission (Fast) VDS

16. Bias-Dependent Trapping Gate: Drain

17. Bias-Dependent FET Model New Parameters

18. Bias-Dependent FET Model Model with quiescent dependence: Model without quiescent dependence: Quiescent-bias dependence allows flexibility in predicting the IV curves.

19. Proposed Upcoming Work • Adapt USF bias-dependent approach for use on other desired models. • Add time-dependence of capture and emission trapping as well as thermal effects. • Develop a straightforward characterization scheme for the bias and time dependence of thermal and trapping effects.

20. Partial Jardel Circuit for Drain Traps* To calculations of backgating voltage + + Vds(t) Vcont(t) _ _ *O. Jardel, F. DeGroote, C. Charbonniaud, T. Reveyrand, J. Teyssier, R. Quere, and D. Floriot, “A Drain-Lag Model for AlGaN/GaN Power HEMTs,” IEEE International Microwave Symposium, Honolulu, Hawaii, June 2007.

21. Radar Power Amplifiers – NRL Proposal • Desire to reduce spectral sidelobes transmitted by shipboard radar systems. • Chireix amplifier topology:

22. Goals and Discussion • Desired Isolation: 100 dB outside of 40 MHz bandwidth • The pulsed signal and nonlinear amplifier use causes additional spectral components  “spectral regrowth”. Reprinted from J. de Graaf, H. Faust, J. Alatishe, and S. Talapatra, “Generation of Spectrally Confined Transmitted Radar Waveforms,” Proc. IEEE Conference on Radar, 2006, pp. 76-83

23. Chireix Amplifier Operation • A method for operating amplifiers with high linearity and efficiency. • Based on a trigonometric identity: G cos[ω(t)+arccos(M(t))] PA Phase Modulated Signals 2GM(t)cos[ω(t)] G cos[ω(t)-arccos(M(t))] PA

24. Combining Challenges • A summer at microwave frequencies? • Combining Techniques • 180-degree coupler • Chireix combiner • A three-port network cannot be lossless, reciprocal, and matched at all ports. • Pros and Cons • 180-degree coupler – matched, reciprocal, and lossy (3 dB) • Chireix combiner – unmatched, reciprocal, and lossless 24

25. 180-Degree Coupler Simulations 25

26. Radar PA Combining – Upcoming Work • Proposal to NRL for $170,000 over 2 years submitted March 2008 • Study different combining techniques: • Examine rejection for better spectral masks. • Continue simulation studies and eventually implement in hardware design improvements. • Meeting with NRL at USF campus on April 14.

27. Phase Noise Prediction • Tremendous consequences for system-level design considerations. • Example: Phase Noise in 64-PSK Amplifier • Transistor 1/f noise is a source of phase noise. • Project Goal: Predicting phase noise accurately in circuits through accurate modeling of 1/f noise.

28. Demonstration Circuits • Linear Amplifier • Test phase noise prediction at multiple bias currents. • Si BJT, SiGe HBT. • Designed circuits presently in test phase. • Frequency Multiplier • Test phase noise prediction due to self-biasing in large-signal operation. • Si BJT, SiGe HBT. • Circuits presently in design phase.

29. Microwaves and Bio – NSF Proposal In collaboration with:

30. Biological Motivation • Tissue composition can often be investigated through permittivity measurements: • Relative Permittivity Shows Three Dispersions: • Alpha Dispersion • Beta Dispersion • Gamma Dispersion Reprinted from H. Schwan, “Electrical Characteristics of Tissues,” Biophysik, 1963, Vol. 1, No. 3, pp. 198-208

31. Dispersions • Alpha Dispersion • In kHz Range • Ionic diffusion (Foster and Schwan) • Measurable with Low Frequency Impedance Analyzer • Beta Dispersion • Between 1 and 100 MHz • Capacitive charging of the cell membrane (Tamura et al.) • Can measure above this with microwave techniques • Delta Dispersion • Varying causes • Between 0.1 and 3 GHz (Foster and Schwan) • Measurable by microwave techniques • Gamma Dispersion • Dipole orientation in water molecules changes (Foster and Schwan) • 20 to 25 GHz (depending on temperature) • Measurable by microwave techniques

32. Measuring the Water Content of Cells • Above the Beta Dispersion, the cell membrane (a capacitor) appears invisible to the electrical signal. • The measured impedance above the Beta Dispersion is heavily dependent upon the water content of the cells. • Cancer cells often have a higher water content than healthy cells (Foster and Schwan).

33. Cell Culture Measurements • Cell cultures often have an impedance of 1 kΩ or higher in the microwave range. • Measuring high impedances with high precision using reflection coefficients is difficult:

34. Microwave Measurement Technique for High Impedances • New technique developed at Czech Technical University: Reprinted from M. Randus and K. Hoffman, “A Simple Method for Extreme Impedances Measurement,” 70th Automatic RF Techniques Group (ARFTG) Conference, Tempe, Arizona, November 2007.

35. Future Research • Presently constructing system to verify method of Randus and Hoffman on large impedances. • Modify cell culture impedance measurement setup of Prof. Shekhar Bhansali to perform microwave measurements. • Examine applications (i.e. clinical detection of cancer)

36. Conclusions • An ambitious first-year approach has allowed expansion of USF’s modeling and characterization program into design and biological applications. • A good industry base has been built, and agency proposals are being generated. • A significant number of publications, as well as additional agency and industry proposals, are expected to be generated from the present work.

37. Acknowledgments • Larry Cohen and Jean de Graaf, Naval Research Laboratory • Christopher Reul, USF • Brent Seward, USF • Nathaniel Varney, USF • Dorielle Price, USF • Dr. Shekhar Bhansali, USF • Dr. Larry Dunleavy, USF and Modelithics, Inc. • Martin Randus, Czech Technical Institute • Dr. Karel Hoffman, Czech Technical Institute

38. Thank you for your time and attention!