Rin transfer technique of optoelectronic noise figure measurement là gì
This example shows how to use RF Blockset™ to measure the Gain and Noise Figure of an RF system over a given spectral range. Show The example requires DSP System Toolbox™. IntroductionIn this example, a method for measuring the frequency-dependent gain and noise figure of an RF system is described. These spectral properties are measured for two RF systems; A single Low Noise Amplifier and the same amplifier when matched. The model used for the measurement is shown below: model = 'GainNoiseMeasurementExample'; open_system(model); The model has two measurement units, each connected to a different subsystem containing the DUT. The upper measurement unit is connected to an unmatched LNA in the DUT subsystem with yellow background: open_system([model '/DUT Unmatched']); The lower measurement unit is connected to a matched LNA in the DUT subsystem with blue background: open_system([model '/DUT Matched']); Each measurement unit outputs two vector signals representing the spectrums of the Gain and Noise Figure of the corresponding DUT and those are inputted into two Array Plot (DSP System Toolbox) blocks that plot the above properties versus frequency, comparing the unmatched and matched DUT systems. In the following sections, the matching network design process is described, the simulation results are given and compared with these expected from LNA and matching network properties. Finally, the procedure used within the measurement units to obtain the spectral Gain and Noise results is explained. Design of the matching networkThe matching network used in the matched DUT subsystem comprises a single stage L-C network that is designed following the same procedure as the one described in the RF Toolbox example Designing Matching Networks for Low Noise Amplifiers. Since the LNA used here is different, the design is described below Initially, an open_system([model '/DUT Unmatched']); 5 object is created to represent an Heterojunction Bipolar Transistor based low noise amplifier that is specified in the file, 'RF_HBT_LNA.S2P'. Then, the open_system([model '/DUT Unmatched']); 6 method of the open_system([model '/DUT Unmatched']); 5 object is used to place the constant available gain and the constant noise figure circles on a Smith chart, and select an appropriate source reflection coefficient, GammaS, that provides a suitable compromise between gain and noise. The GammaS value chosen yields an available gain of Ga=21dB, and a noise figure of NF=0.9dB at the center frequency fc=5.5GHz: unmatched_amp = read(rfckt.amplifier, 'RF_HBT_LNA.S2P'); fc = 5.5e9; % Center frequency (Hz) circle(unmatched_amp,fc,'Stab','In','Stab','Out','Ga',15:2:25, ... % Choose GammaS and show it on smith chart:
hold on
GammaS = 0.411*exp(1j*106.7*pi/180);
plot(GammaS,'k.','MarkerSize',16)
text(real(GammaS)+0.05,imag(GammaS)-0.05,'\Gamma_{S}','FontSize', 12, ... hLegend = legend('Location','SouthEast');
hLegend.String = hLegend.String(1:end-1);
hold offFor the chosen GammaS, the following properties can be obtained: % Normalized source impedance: Zs = gamma2z(GammaS,1); % Matching |GammaL| that is equal to the complex conjugate of % |GammaOut| shown on the data tip: GammaL = 0.595*exp(1j*135.0*pi/180); % Normalized load impedance: Zl = gamma2z(GammaL,1); The input matching network consists of one shunt capacitor, Cin, and one series inductor, Lin. The Smith chart is used to find the component values. To do this, the constant conductance circle that crosses the center of the Smith chart and the constant resistance circle that crosses open_system([model '/DUT Unmatched']); 8 are plotted and the intersection points (Point [~, hsm] = circle(unmatched_amp,fc,'G',1,'R',real(Zs)); hsm.Type = 'YZ'; % Choose GammaA and show points of interest on smith chart: hold on plot(GammaS,'k.','MarkerSize',16) text(real(GammaS)+0.05,imag(GammaS)-0.05,'\Gamma_{S}','FontSize', 12, ... plot(0,0,'k.','MarkerSize',16)
GammaA = 0.384*exp(1j*(-112.6)*pi/180);
plot(GammaA,'k.','MarkerSize',16)
text(real(GammaA)+0.05,imag(GammaA)-0.05,'\Gamma_{A}','FontSize', 12, ... hLegend = legend('Location','SouthEast');
hLegend.String = hLegend.String(1:end-3);
hold offUsing the chosen GammaA, the input matching network components, Cin and Lin, are obtained: % Obtain admittance Ya corresponding to GammaA: Za = gamma2z(GammaA,1); Ya = 1/Za; % Using Ya, find Cin and Lin: Cin = imag(Ya)/50/2/pi/fc Lin = (imag(Zs) - imag(Za))*50/2/pi/fc Cin = 4.8145e-13 Lin = 1.5218e-09 In a similar manner, the output matching network components are obtained using the intersection points (Point open_system([model '/DUT Unmatched']); 9: [hLine, hsm] = circle(unmatched_amp,fc,'G',1,'R',real(Zl)); hsm.Type = 'YZ'; % Choose GammaB and show points of interest on smith chart: hold on plot(GammaL,'k.','MarkerSize',16) text(real(GammaL)+0.05,imag(GammaL)-0.05,'\Gamma_{L}','FontSize', 12, ... plot(0,0,'k.','MarkerSize',16)
GammaB = 0.612*exp(1j*(-127.8)*pi/180);
plot(GammaB,'k.','MarkerSize',16)
text(real(GammaB)+0.05,imag(GammaB)-0.05,'\Gamma_{B}','FontSize', 12, ... hLegend = legend('Location','SouthEast');
hLegend.String = hLegend.String(1:end-3);
hold offUsing the chosen GammaB, the input matching network components, Cout and Lout, are obtained: % Obtain admittance Yb corresponding to GammaB: Zb = gamma2z(GammaB, 1); Yb = 1/Zb; % Using Yb, find Cout and Lout: Cout = imag(Yb)/50/2/pi/fc open_system([model '/DUT Unmatched']); 0 Simulation results for gain and noise figure spectrum measurement modelThe above input and output network component values are used in the simulation of the matched DUT in the gain and noise figure spectrum measurement model described earlier. The spectral results displayed in the Array Plot blocks are given below: open_system([model '/DUT Unmatched']); 1 Next, the simulation results are compared with those expected analytically. To facilitate the comparison, the unmatched and matched amplifier networks are analyzed using RF Toolbox. In addition, as finer details are required, the simulation is run for a longer time. The results of the longer simulation are given in the file 'GainNoiseResults.mat'. open_system([model '/DUT Unmatched']); 2 Operation of the measurement unitThe measurement unit produces an input signal, DUT_in, that is composed of zero-mean white noise and zero-variance impulse response signal. The latter is used to determine the frequency response of the DUT gain and together with the white noise determine the DUT noise figure. The measurement unit collects the DUT output signal, performs a windowed FFT on it and then facilitates statistical calculations to obtain the gain and the noise figure of the DUT. open_system([model '/DUT Unmatched']); 3 The statistical calculations are done in the area marked in blue. The calculations use three inputs in the frequency domain; Input Noise Only, Input Signal Only, and Output Signal. The Input Signal Only is compared with the mean of the Output Signal to determine the DUT's gain, Where, The properties affecting the operation of the measurement unit are specified in the block's mask parameter dialog box as shown below: These parameters are described below:
Gain tolerance - The threshold of gain variation relative to its average. When the threshold is hit, the gain is considered as converged, triggering a reset for the output noise calculation. |