About SNDR in pipelined ADC

[ronanchang]

adc sndr

The ADC is 10bit 80Ms/s,How can I use FFT to get the SNDR ?
Should I have to do the FFT in D0 D1 D2 ~~D9??
The input is a full-scale sinewave.

 

[Vamsi Mocherla]

Why dont you have an ideal behavioural model of a DAC? Then the output of the DAC can be subjected to FFT.

 

[ronanchang]

can I use voltage-control-current-source to get the analog input.
then take this reconstructive signal to do FFT??

 

[Vamsi Mocherla]

You can write a simple code for a DAC. You can have a small MatLab code, where every LSB step will give you an analog output.

 

[zwei78]

You can input a sine wave that frequency is less than 40MHz. And you can get many 10bit digital output datas. You must simulate or test many periods. You can use this matlab file to caculate your SNR SNDR and THD SFDR.

fclk=80E+6;
numpt=4096;
numbit=10;
load saradcdata.txt; % Load data from disk;
a=saradcdata';
N=length(a);
%[M,N]=size(a); % Number of data;
for i=1:1:N; %
c=int2str(a(i)); % Change integer type data to string type;
temp=0; %
Nlength=length(c); % Length of the string;
for j=1:1:Nlength; %
d=str2num(c(j))*2^(Nlength-j); % Binary to decimalization
temp=temp+d; %
end; %
code(i)=temp/4096*2.5; %
end;
%N=length(code);
%Display a warning, when the input generates a code greater than full-scale
%if (max(code)==2^numbit-1) | (min(code)==0)
%disp('Warning: ADC may be clipping!!!');
%end
%Plot results in the time domain
figure;
plot([1:N],code);
title('TIME DOMAIN')
xlabel('SAMPLES');
ylabel('DIGITAL OUTPUT CODE');
zoom xon;
%Recenter the digital sine wave
Dout=code
%-(2^numbit-1)/2;
%If no window function is used, the input tone must be chosen to be unique and with
%regard to the sampling frequency. To achieve this prime numbers are introduced and the
%input tone is determined by fIN = fSAMPLE * (Prime Number / Data Record Size).
%To relax this requirement, window functions such as HANNING and HAMING (see below) can
%be introduced, however the fundamental in the resulting FFT spectrum appears 'sharper'
%without the use of window functions.
Doutw=Dout;
%Doutw=Dout.*hanning(numpt);
%Doutw=Dout.*hamming(numpt);
%Performing the Fast Fourier Transform
Dout_spect=fft(Doutw,numpt);
%Recalculate to dB
Dout_dB=20*log10(abs(Dout_spect));
%plot([1:N/2],Dout_dB(1:N/2));
%Display the results in the frequency domain with an FFT plot
figure;
maxdB=max(Dout_dB(2:numpt/2));
%For TTIMD, use the following short routine, normalized to —6.5dB full-scale.
%plot([0:numpt/2-1].*fclk/numpt,Dout_dB(1:numpt/2)-maxdB-6.5);
plot([0:numpt/2-1].*fclk/numpt,Dout_dB(1:numpt/2)-maxdB);
grid on;
title('FFT PLOT');
xlabel('ANALOG INPUT FREQUENCY (MHz)');
ylabel('AMPLITUDE (dB)');
a1=axis; axis([a1(1) a1(2) -120 a1(4)]);
%Calculate SNR, SINAD, THD and SFDR values
%Find the signal bin number, DC = bin 1
fin=find(Dout_dB(1:numpt/2)==maxdB);
%Span of the input frequency on each side
%span=5;
span=max(round(numpt/200),5);
%Approximate search span for harmonics on each side
spanh=2;
%Determine power spectrum
spectP=(abs(Dout_spect)).*(abs(Dout_spect));
%Find DC offset power
Pdc=sum(spectP(1:span));
%Extract overall signal power
Ps=sum(spectP(fin-span:fin+span));
%Vector/matrix to store both frequency and power of signal and harmonics
Fh=[];
%The 1st element in the vector/matrix represents the signal, the next element represents
%the 2nd harmonic, etc.
Ph=[];
%Find harmonic frequencies and power components in the FFT spectrum
for har_num=1:10
%Input tones greater than fSAMPLE are aliased back into the spectrum
tone=rem((har_num*(fin-1)+1)/numpt,1);
if tone>0.5
%Input tones greater than 0.5*fSAMPLE (after aliasing) are reflected
tone=1-tone;
end
Fh=[Fh tone];
%For this procedure to work, ensure the folded back high order harmonics do not overlap
%with DC or signal or lower order harmonics
har_peak=max(spectP(round(tone*numpt)-spanh:round(tone*numpt)+spanh));
har_bin=find(spectP(round(tone*numpt)-spanh:round(tone*numpt)+spanh)==har_peak);
har_bin=har_bin+round(tone*numpt)-spanh-1;
Ph=[Ph sum(spectP(har_bin-1:har_bin+1))];
end
%Determine the total distortion power
Pd=sum(Ph(2:5));
%Determine the noise power
Pn=sum(spectP(1:numpt/2))-Pdc-Ps-Pd;
format;
A=(max(code)-min(code))
%/2^numbit
AdB=20*log10(A)
SINAD=10*log10(Ps/(Pn+Pd))
SNR=10*log10(Ps/Pn)
disp('THD is calculated from 2nd through 5th order harmonics');
THD=10*log10(Pd/Ph(1))
SFDR=10*log10(Ph(1)/max(Ph(2:10)))
disp('Signal & Harmonic Power Components:');
HD=10*log10(Ph(1:10)/Ph(1))
%Distinguish all harmonics locations within the FFT plot
hold on;
plot(Fh(2)*fclk,0,'mo',Fh(3)*fclk,0,'cx',Fh(4)*fclk,0,'r+',Fh(5)*fclk,0,'g*',Fh(6)

*fclk,0,'bs',Fh(7)*fclk,0,'bd',Fh(8)*fclk,0,'kv',Fh(9)*fclk,0,'y^');
legend('1st','2nd','3rd','4th','5th','6th','7th','8th','9th');
%hold off;
%Dynamic-Range Specifications, TTIMD
%Two-tone IMD can be a tricky measurement, because the additional equipment required (a

power combiner to combine two input frequencies) can contribute unwanted intermodulation

products that falsify the ADC's intermodulation distortion. You must observe the following

conditions to optimize IMD performance, although they make the selection of proper input

frequencies a tedious task.
%First, the input tones must fall into the passband of the input filter. If these tones are

close together (several tens or hundreds of kilohertz for a megahertz bandwidth), an

appropriate window function must be chosen as well. Placing them too close together,

however, may allow the power combiner to falsify the overall IMD readings by contributing

unwanted 2nd- and 3rd-order IMD products (depending on the input tones' location within the

passband). Spacing the input tones too far apart may call for a different window type that

has less frequency resolution.
%The setup also requires a minimum of three phase-locked signal generators. This requirement

seldom poses a problem for test labs, but generators have different capabilities for

matching frequency and amplitude. Compensating such mismatches to achieve (for example) a -

0.5dB FS two-tone envelope and signal amplitudes of -6.5dB FS will increase your effort and

test time (see the following program-code extraction).
%For TTIMD, use the following short routine, normalized to -6.5dB full-scale.
%plot([0:numpt/2-1].*fclk/numpt,Dout_dB(1:numpt/2)-maxdB-6.5);
plot([0:numpt/2-1].*fclk/numpt,Dout_dB(1:numpt/2)-maxdB);
grid on;
title('FFT PLOT');
xlabel('ANALOG INPUT FREQUENCY (MHz)');
ylabel('AMPLITUDE (dB)');
a1=axis; axis([a1(1) a1(2) -120 a1(4)]);

 

[ronanchang]

dear zwei78,
Thanks for your opinion.

 

[wany]

how to save the spectre as text file ?

Added after 1 hours 14 minutes:

how to save the spectre as text file ?

 

[flushrat]

how to save the spectre as text file ?

Added after 1 hours 14 minutes:

how to save the spectre as text file ?

use ocnPrint function in ciw

 

[avinash]

dear zwei78,
can you please give the matlab code for calculating the SNR of 16-bit sigma delta ADC.actually i do have the bitsteam o/p of the modulator.now this bitsteam has to be passed through the decimator .but i want these bitstream to be paased thruogh the low pass filter using matlab,for which ,i need the codes.moreover by passing these bitsteam thruogh low pass filter,can i get the 16-bit response and SNR of 98dB (assuming the bitstreams are the o/p of ideal ΣΔ modulator).

 

[jennisjose]

i agree with Vamsi's answer, that wht i used in my project.

I have included as much schematics as possible.

https://jennisjose.webs.com/pipelinedadc.htm