微波仿真论坛加州大学RF功放设计实例.ppt

1 Power Amplifier Nonlinearity Estimation and Predistortion with Correlation Techniques Mingyuan Li, Ian Galton, Larry Larson, Peter Asbeck University of California, San Diego La Jolla, CA 92093-0407 2 Outline lNonlinearity extraction in frequency and time domain lCorrelation techniques for nonlinearity estimation lMathematical analysis and simulation results lApplication in adaptive predistortion and measured results lSummary and conclusion 3 AM-AM and AM-PM nonlinearity Measurement of Intersils ISL3990 Dual Band PA Look Up Table behavioral model Behavioral model Complex polynomial curve fitting model Single tone and two-tone power sweep measurement Gain and phase vs input power Gain and phase values vs envelope amplitude r(t) Pro: Simple to characterize and analyze nonlinearity Con: 1. Not actual signal 2. Cant test during normal operation conditions Intermodulations vs input power 4 Pro: Actual signal, test during PA operation Con: 1. High resolution and speed ADC 2. Large memory 3. Considerable DSP Time-domain CDMA envelope test Gain vs. Pin using time-domain captured dataPhase vs. Pin using time-domain captured data Vout (red) vs. vin(blue) (a) real part (b) imaginary part (a) (b) Assess nonlinearity in adaptive predistortion 5 Correlation techniques for nonlinearity estimation Basic idea Nonlinearity comes from output with 3rd,5th order dependency on input. Create test signal which also has 3rd,5th order dependency on input. Extract nonlinearity by proper correlation of output and test signal Advantages Actual signal in real operation conditions Low hardware and power consumption Stest is uncorrelated with linear(Vin) Stest is correlated with nonliear(Vin) DS-CDMA +X LO X PA Correlation PA nonlinearity S1 S2 S3 Stest Stest=S1*S2*S3 +1 -1 Vout=Linear(Vin)+Nonlinear(Vin) Vin 6 Correlation mathematical analysis dominant Stest termsnon Stest terms average to zero lAssumptions Quasi-memoryless Polynomial model truncated at the 5th order Correlation 7 Application to IS-95 forward link transmitter I XI 8 Complex power series analysis Real correlation valueImag correlation value Power correlation value Polynomial coefficients extraction by correlation 9 Comparison of correlation with other techniques Construct AM_AM and AM_PM using polynomial coefficients derived by correlations Different order with different slopes Comparison of two-tone and correlation 10 Correlation experimental measurements Intersils ISL3990 PA 5 Channel PN with 48-tap FIR and Length is 217 Sampling rate is 4*1.2288MHz (a)First order II (b)Third order IQ(c) Fifth order II(d)Power correlation vs. Pin 11 Adaptive predistortion application Predistortion architecture Using the correlation extracted values P3corr and P5corr as an object function to adaptively change predistorters coefficients 12 Adaptive search algorithm(Hooke &Jeeves) Contour of correlation values vs. predistortion coefficients 13 Measurement results (1) Amplifier before predistortion is at (b3r,b3i,b5r,b5i=0) pointPin=-10dBm 3rd correlation values(dB) vs. b3 3rd correlation values(dB) vs. b5 Acpr750kHz(dBc) vs. b3 Acpr750kHz(dBc) vs. b5 ISL3990 PA P1db= -10dBm Psat=10dBm Pmax=24.5dBm 14 Measurement results (2) Magenta curve has larger correlation values and worse ACPR Green curve has smaller correlation values and better ACPR ACPR difference of 14.3dB750kHz 4.8dB1980kHz before PD after PD Magenta before PD, Green after PD Pin=-10dBm 15 Summary and conclusion lSimple correlation techniques have been used to estimate nonlinearity lSimulation and measurement results show promise of technique lApplication in forward link adaptive predistortion transmitter was shown experime