calculateSNR
Signal-to-noise ratio based on in-band bins of windowed FFT and location of input
Since R2026a
Description
Examples
Define a second-order delta-sigma modulator and the system parameters for the simulation.
order = 2; % The "Order" of the modulator OSR = 64; % Oversampling Ratio (fs / 2*BW) nlev = 2; % Number of quantizer levels (2 = Binary: +1 or -1) N = 2^14; % Number of points for the FFT simulation (16,384) test_freq = 5; % The bin index for our test sine wave (must be an integer)
Determine the in-band frequency range for SNR calculation.
fB = floor(N/(2*OSR));
Synthesize the noise transfer function (NTF). This creates a mathematical filter that pushes noise to high frequencies.
ntf = synthesizeNTF(order, OSR);
Realize the NTF as a CIFB circuit topology.
[a, g, b, c] = realizeNTF(ntf, 'CIFB');Create the state-space matrix for the simulator.
abcd = stuffABCD(a, g, b, c, 'CIFB');Scale the ABCD matrix so that the internal voltages stay within the range of the quantizer.
[abcd_scaled, umax] = scaleABCD(abcd, nlev);
To set up the simulation, define a range of input amplitudes to test, from very quiet to loud. Run simulation.
amp_db = -110:10:-10; % Decibels relative to Full Scale (dBFS) amp_lin = 10.^(amp_db/20); % Convert dB to linear voltage snr_sim = zeros(size(amp_db)); % Pre-allocate space for results for i = 1:length(amp_db) % Generate a test sine wave at the current amplitude t = 0:N-1; u = amp_lin(i) * sin(2*pi*test_freq/N * t); % Run the Delta-Sigma Modulator Simulation % Returns 'v', which is the high-speed 1-bit output bitstream. v = simulateDSM(u, abcd_scaled, nlev); % Spectral Analysis: % 1. Apply a Hann window to prevent spectral leakage w = ds_hann(N); % 2. Perform the FFT V = fft(v .* w); % 3. Calculate SNR of the in-band portion % calculateSNR sums signal power at 'test_freq' and noise in remaining bins. snr_sim(i) = calculateSNR(V(1:fB), test_freq); end
Predict the theoretical SNR. Calculate a peak value to anchor the predicted SNR curve.
peak_snr_theory = 10*log10( ((2*order+1)/(2*pi^(2*order))) * (OSR^(2*order+1)) ); snr_pred = peak_snr_theory + amp_db;
Plot the predicted and simulated SNR.
figure('Color', 'w', 'Name', 'Delta-Sigma Performance'); % Plot the Theoretical Limit (The Blue Line) plot(amp_db, snr_pred, 'b-', 'LineWidth', 2); hold on; % Plot the Actual Simulated Results (The Red Dots) plot(amp_db, snr_sim, 'ro', 'MarkerFaceColor', 'r', 'MarkerSize', 8); % Formatting the plot grid on; axis([-125 5 -20 120]); % Set fixed view for comparison xlabel('Input Amplitude (dBFS)'); ylabel('SNR (dB)'); title(sprintf('Order %d Delta-Sigma Modulator (OSR=%d)', order, OSR)); legend('Predicted Theory (Ideal)', 'Simulated Bitstream', 'Location', 'SouthEast');

Input Arguments
Input spectrum data, specified as a vector or array containing the frequency-domain
coefficients. hwfft represents the in-band bins of the FFT of the
output signal of the delta-sigma modulator.
Data Types: double
Input signal frequency adjusted to be an FFT bin, specified as a real scalar.
f represents the location of the input test tone within the
hwfft vector.
Data Types: double
Number of signal bins, specified as a positive integer scalar.
nsig determines how many bins surrounding the peak index
f are treated as signal power rather than noise. By default, the
function assumes the signal power is contained within a three-bin window where
nsig is set to 1. Increasing nsig by 1 adds
one extra bin to each side of this window.
Data Types: double
Output Arguments
Signal-to-noise ratio (SNR) of the delta-sigma modulator within the frequency range provided by the input spectrum, returned as a scalar.
Version History
Introduced in R2026a
See Also
calculateTF | synthesizeNTF | realizeNTF | stuffABCD | mapABCD | scaleABCD | predictSNR | simulateSNR | simulateDSM
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