Matlab Analyze Ams Waveform

Analyze AMS Waveforms — Mixed-Signal Blockset Utilities

Analyze waveform data using msblksutilities functions from the Mixed-Signal Blockset. Covers timing, phase noise, jitter, lock time, resampling, INL/DNL, ADC/DAC calibration, and HSpice data import.

When to Use

• Measuring phase noise from time-domain VCO/PLL simulation output
• Computing period jitter or cycle-to-cycle jitter from clock signals
• Resampling non-uniform (variable-step solver) data to a uniform grid
• Measuring rise/fall time, duty cycle from digital waveforms
• Computing INL/DNL for ADC/DAC characterization
• Importing HSpice simulation results (.tr0, .ac0, .sw0)
• Converting a phase noise profile to integrated RMS jitter

When NOT to Use

• Spectral analysis with Signal Processing Toolbox (FFT, PSD, spectrogram) — use SPT directly
• Signal quality metrics (SNR, SINAD, THD, SFDR) — use SPT functions (snr, thd, sfdr, sinad) directly
• Filtering or envelope detection — use Signal Processing Toolbox directly
• Uniformly-sampled data that doesn't need anti-aliased resampling

Workflow Directive: Phase Noise Parameter Gathering

When the user asks to measure phase noise from waveform data, ask for frequency offset points before proceeding:

1. Ask: "At which frequency offsets would you like to measure phase noise? Default: [10e3, 100e3, 1e6, 10e6] Hz — press Enter to use these or specify your own."
2. Once offsets are confirmed, propose RBW based on the lowest offset: RBW = min(offsets) / 2 (e.g., 5 kHz for 10 kHz lowest offset). State: "I'll use RBW = X Hz (lowest offset / 2). Let me know if you'd like a different value."
3. Proceed with measurement unless the user overrides.

This ensures the measurement matches the user's application without requiring them to know the API signature upfront.

Phase 1: Ingest Waveform Data

1.1 Determine Data Source

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% From workspace variables
x = t;  y = v;

% From .mat file
data = load('waveform.mat');
x = data.time;  y = data.voltage;

% From .csv
data = readmatrix('waveform.csv');
x = data(:,1);  y = data(:,2);

% From HSpice transient (.tr0)
tr0Reader('sim.tr0', 'output.mat');
data = load('output.mat');

% From HSpice AC (.ac0)
ac0Reader('sim.ac0', 'output.mat');

% From HSpice DC sweep (.sw0)
sw0Reader('sim.sw0', 'output.mat');

% From Simulink simulation output (timeseries in logsout)
sig = simOut.logsout.get('signalName').Values;
x = sig.Time(:);          % column vector
y = squeeze(sig.Data(:)); % column vector — squeeze removes trailing dims

1.2 Basic Waveform Summary

Always print a summary before analysis:

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fprintf('=== Waveform Summary ===\n');
fprintf('Points     : %d\n', numel(x));
fprintf('X range    : [%.6g, %.6g]\n', min(x), max(x));
fprintf('Y range    : [%.6g, %.6g]\n', min(y), max(y));
fprintf('Y mean     : %.6g\n', mean(y));
fprintf('Y RMS      : %.6g\n', rms(y));
if all(diff(x) > 0)
    dx = diff(x);
    if max(dx)/min(dx) < 1.01, uStr = 'yes'; else, uStr = 'no'; end
    fprintf('X step     : %.6g (uniform: %s)\n', median(dx), uStr);
    if median(dx) > 0
        fprintf('Sample rate: %.6g Hz\n', 1/median(dx));
    end
end

1.3 MSB Analysis Menu

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Available MSB analyses for time-domain waveform:

  --- Timing Measurements ---
  [1]  Rise time — timeDomainSignal2RiseTime
  [2]  Fall time — timeDomainSignal2FallTime
  [3]  Duty cycle — timeDomainSignal2DutyCycle

  --- Clock / PLL Measurements ---
  [4]  Phase noise from frequency-domain data — phaseNoiseMeasure (default Type='Frequency')
  [5]  Phase noise from time-domain voltage — phaseNoiseMeasure (Type='Time')
  [6]  Period jitter & cycle-to-cycle jitter — clockJitterMeasure
  [7]  Phase noise to jitter conversion — phaseNoiseToJitter
  [8]  Lock time from control voltage — lockTimeMeasure

  --- Resampling ---
  [9]  Anti-aliased resampling — lowpassResample

  --- ADC/DAC Characterization ---
  [10] INL / DNL measurement — inldnl
  [11] ADC calibration — calibrateADC
  [12] DAC calibration — calibrateDAC

  --- Data Import ---
  [13] HSpice transient (.tr0) — tr0Reader
  [14] HSpice AC (.ac0) — ac0Reader
  [15] HSpice DC sweep (.sw0) — sw0Reader

  --- Frequency-Domain Utilities ---
  [16] Interpolate/extrapolate to new grid — interpExtrap
  [17] Laplace to biquad SOS — laplace2sos

Phase 2: Execute Analysis

2.1 Timing Measurements

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% Rise time — 3rd arg is [low high] percent reference levels (required)
rt = timeDomainSignal2RiseTime(x, y, [10 90]);
fprintf('Rise time (10%%-90%%): mean = %.4g s (std = %.4g s, N=%d)\n', ...
    mean(rt), std(rt), numel(rt));

% Fall time — same 3-arg signature
ft = timeDomainSignal2FallTime(x, y, [10 90]);
fprintf('Fall time (90%%-10%%): mean = %.4g s (std = %.4g s, N=%d)\n', ...
    mean(ft), std(ft), numel(ft));

% Duty cycle — returns per-cycle values for multi-cycle waveforms
dc = timeDomainSignal2DutyCycle(x, y);
fprintf('Duty cycle: mean = %.4f%%, std = %.4f%%\n', mean(dc)*100, std(dc)*100);

2.2 Phase Noise Measurement

Pre-check (mandatory): Verify simulation duration before measuring.

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% Sim duration pre-check — STOP if insufficient
minDuration = 10 / min(FrOffset);   % need >= 10 cycles of lowest offset
simDuration = x(end) - x(1);
if simDuration < minDuration
    error('Simulation too short: %.4g s < %.4g s needed for %.0f Hz offset.\nIncrease sim stop time to >= %.4g s.', ...
        simDuration, minDuration, min(FrOffset), minDuration);
end

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% From time-domain voltage waveform (MSB variable-step simulation output)
% Type='Time' is REQUIRED — extracts phase via zero-crossings internally
Rbw = 1e3;                          % resolution bandwidth (Hz)
FrOffset = [10e3 100e3 1e6 10e6];   % offsets to measure
[PnAtOffsets, freqAxis, pnProfile] = phaseNoiseMeasure( ...
    x(:), y(:), Rbw, FrOffset, 'on', 'PN Measurement', ...
    -inf, ...                       % 7th arg: target PN level for plot overlay (-inf = no target line)
    Type='Time');
% Note: To reduce ripple in pnProfile, use smaller RBW (increases freq resolution)
% or increase simulation duration. SpectralAverages is a PLL Testbench block
% parameter, NOT a phaseNoiseMeasure argument.

% From frequency-domain data (e.g., imported spectrum analyzer measurement)
% Default Type='Frequency': Xin=freq offset vector, Yin=power in dBc/Hz
[PnAtOffsets, freqAxis, pnProfile] = phaseNoiseMeasure( ...
    freqOffsets, pnPower_dBcHz, Rbw, FrOffset, 'on', 'PN from Spectrum');

fprintf('Phase Noise Results:\n');
for k = 1:numel(FrOffset)
    fprintf('  @ %.0f kHz : %.1f dBc/Hz\n', FrOffset(k)/1e3, PnAtOffsets(k));
end

% Save figure for Claude to read
figPath = fullfile(tempdir, 'phase_noise_plot.png');
saveas(gcf, figPath);
fprintf('Phase noise figure saved to: %s\n', figPath);

2.3 Jitter Measurements

Mandatory follow-up: After any phase noise measurement (Section 2.2), ALWAYS compute integrated RMS jitter using phaseNoiseToJitter. Report jitter in picoseconds — this is the metric engineers compare against specs.

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% Clock jitter from time-domain waveform
% Returns 2 outputs: [periodJitter, c2cJitter] (RMS values)
% threshold MUST cross the signal — use midpoint or known logic level
% Inputs must be column vectors
threshold = (max(y) + min(y)) / 2;
clockFreq = 1e9;     % expected clock frequency (Hz)
[periodJitter, c2cJitter] = clockJitterMeasure(x(:), y(:), threshold, clockFreq);
fprintf('Period jitter (RMS): %.4f ps\n', periodJitter * 1e12);
fprintf('C2C jitter (RMS)   : %.4f ps\n', c2cJitter * 1e12);

% Convert phase noise profile to jitter
% Exclude DC bin (freqAxis==0) — integration from 0 Hz returns Inf
validIdx = freqAxis > 0;
[jitterRad, jitterDeg, jitterSec] = phaseNoiseToJitter( ...
    freqAxis(validIdx), pnProfile(validIdx), Frequency=carrierFreq);
fprintf('RMS jitter from PN : %.4f ps\n', jitterSec * 1e12);

2.4 Lock Time Measurement

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% x = time, y = control voltage (loop filter output)
% lockTimeMeasure takes (voltage, time, tolerance) — note: voltage FIRST
% Both must be column vectors
x_col = x(:);  y_col = y(:);
targetVoltage = y_col(end);   % assume final value is lock voltage
errorTol = 0.01;              % 1% tolerance
lockTime = lockTimeMeasure(y_col, x_col, errorTol);
fprintf('Lock time (%.0f%% tolerance): %.4g s\n', errorTol*100, lockTime);

Preferred method: If a PLL Testbench block is present, use its measured lock time (get_param(tbBlk, 'UserData').lockTime) — frequency-error detection is more accurate than voltage settling.

2.5 Resampling

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% Anti-aliased resampling to new sample time
Ts_new = 1e-9;
tq = (x(1) : Ts_new : x(end))';
cfg.OutputRiseFall = Ts_new;
cfg.NDelay = 1;
cfg.SampleMode = 'variable';
cfg.CausalMode = 'off';
y_resampled = lowpassResample(x, y, tq, cfg);
x_resampled = tq;

2.6 INL/DNL Measurement

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% ADC: uses transition-based fit (works on ANY input stimulus, not just ramps)
result = inldnl(Analog, Digital, Range, 'ADC', ...
    'INLMethod', 'All', 'DNLMethod', 'All', ...
    'OffsetErrorUnit', 'All', 'GainErrorUnit', 'All');

fprintf('Max |Endpoint INL|: %.4f LSB\n', max(abs(result.EndpointINL)));
fprintf('Max |Endpoint DNL|: %.4f LSB\n', max(abs(result.EndpointDNL)));
fprintf('Offset Error: %.4f LSB\n', result.OffsetErrorLSB);
fprintf('Gain Error: %.4f LSB\n', result.GainErrorLSB);

% DAC: uses center-based fit (FitMode='centers' is default for DAC)
result_dac = inldnl(Analog, Digital, Range, 'DAC', ...
    'INLMethod', 'All', 'DNLMethod', 'All');

Critical: Do NOT use histogram-based DNL (code bin counts). That method requires a specific input stimulus (ramp or sine with known PDF). The inldnl function uses transition-based analysis that works on arbitrary inputs.

ADC vs DAC: ADC uses FitMode='transitions' (default); DAC uses FitMode='centers'. Using the wrong fit mode gives incorrect results.

2.7 ADC/DAC Calibration

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% Calibrate ADC: correct offset and gain errors
y_cal = calibrateADC(Digital, NBits, Polarity);
% Or infer errors from measured data:
y_cal = calibrateADC(Analog, Digital, Range, 'OffsetError', oe, 'GainError', ge);

% Calibrate DAC:
y_cal = calibrateDAC(Digital, NBits, Polarity);
% Or with reference/bias:
y_cal = calibrateDAC(Digital, Analog, Ref, Bias);

Phase 3: Interpreting Phase Noise Plots

3.1 Slope Analysis

3.2 Loop Bandwidth Hump

A hump or peak (3-10 dB) indicates the PLL closed-loop bandwidth. If >10 dB, the loop may be under-damped (low phase margin).

3.3 Noise Floor

Far-out floor (beyond 1-10 MHz offset) is set by VCO thermal noise and simulation numerical noise. Should match VCO open-loop spec.

3.4 Artifacts and Ripple

• High-frequency ripple: Insufficient spectral averaging
• Spurious tones: Expected at multiples of fPFD in frac-N PLLs
• Flat/rising at low offsets: Simulation too short (see W9)

3.5 Example Interpretation

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Phase noise from a 1 GHz VCO (MSB sim, 100 us, zero-crossing):
  @ 10 kHz  : -51.8 dBc/Hz  <- marginal (sim too short)
  @ 100 kHz : -82.4 dBc/Hz  <- in 1/f^2 region, reasonable
  @ 1 MHz   : -98.4 dBc/Hz  <- approaching noise floor
  @ 10 MHz  : -127.6 dBc/Hz <- VCO open-loop thermal floor

Observations:
- -20 dB/dec slope from 10-80 kHz confirms white FM noise
- Hump at 100-300 kHz suggests loop BW artifact
- Floor at -128 dBc/Hz consistent with VCO open-loop spec
- 10 kHz result unreliable -- need >= 1 ms sim for clean data

Phase 4: Reporting

4.1 Save Figure for Inspection

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figPath = fullfile(tempdir, 'analysis_plot.png');
saveas(gcf, figPath);
fprintf('Figure saved to: %s\n', figPath);

After MATLAB prints figPath, use the Read tool to open the PNG and provide observations (slope, artifacts, noise floor per Phase 3).

4.2 Generate HTML Report

Always generate an HTML report with:

1. Header (data file, date, method, MATLAB version)
2. MATLAB console output in dark-themed <pre> block
3. Waveform summary table
4. Measurement config table
5. Numeric results table
6. Embedded figure via file:/// URL
7. Observations from Phase 3
8. Recommendations
9. Footer: "Generated by Claude Code -- Waveform Analysis Skill -- {date}"

Naming: report_{datafile_stem}.html in the same directory as the data.

Quick Reference: MSB Function Sources

Pitfalls (MSB-specific)

• W1: Always compute Fs from data (1/median(diff(x))) rather than assuming
• W2: For phase noise, RBW should be <= half the lowest offset frequency
• W3: For time-domain voltage data (MSB sim output), always pass Type='Time'. The only valid types are 'Frequency' (default) and 'Time'
• W4: For non-uniformly sampled data, resample to uniform grid first using lowpassResample
• W5: clockJitterMeasure needs the nominal clock frequency from design spec, not estimated from data
• W6: HSpice readers output .mat files -- load them after conversion
• W7: MSB uses variable-step discrete solver, producing non-uniform time data. Voltage-based FFT methods will fail — always use phaseNoiseMeasure(..., Type='Time') which extracts phase via zero-crossings internally
• W8: Zero-crossing phaseNoiseMeasure reports center frequency as f_carrier/2 -- this is a display convention, carrier is still correct
• W9: Simulation duration limits lowest measurable offset: need >= 10/f_offset_min seconds. E.g., 10 kHz offset requires >= 1 ms sim time
• W10: PN profile ripple is reduced by using smaller RBW or longer simulation duration. SpectralAverages is a PLL Testbench block parameter (set via set_param), NOT a phaseNoiseMeasure argument
• W11: MSB variable-step data shows max(dt)/min(dt) >> 1. This is expected — use Type='Time' for PN, or lowpassResample to create a uniform grid for FFT
• W12: clockJitterMeasure returns NaN if threshold doesn't cross the signal. Use (max(y)+min(y))/2 or the known logic threshold
• W13: phaseNoiseToJitter returns Inf if freqAxis(1)==0. Always exclude the DC bin before calling
• W14: NEVER use histogram-based DNL on MSB simulation data. MSB outputs are not uniform ramps — histogram method gives 1000x+ errors. Always use inldnl(Analog, Digital, Range, Type) which uses transition detection
• W15: For ADC use FitMode='transitions' (default). For DAC use FitMode='centers'. Using the wrong fit mode corrupts INL results
• W16: All MSB measurement functions (lockTimeMeasure, clockJitterMeasure, phaseNoiseMeasure Type='Time') expect column vectors. Use x(:) and y(:) to ensure correct shape. Row vectors produce silent wrong results or errors

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