Matlab Detect Capture Usrp

%% Energy Detection - Adaptive Threshold
% Detect and capture signal when energy increases above threshold.
clear ed pd
radioName = "MyN310";              % <- set: your radio configuration name
ed = energyDetector(radioName);

% Configure RF parameters
ed.CenterFrequency = 2.45e9;       % <- set: Hz
ed.SampleRate = 30.72e6;           % <- set: Hz
ed.RadioGain = 30;                 % <- set: dB (device-dependent range)
ed.CaptureDataType = "double";

% Configure adaptive threshold
ed.ThresholdMethod = "adaptive";
ed.MinimumEnergy = 0.1;            % <- set: energy floor [0, 8191]; use 0 over loopback (let the dB delta trigger)
ed.EnergyDeltaThreshold = 3;       % <- set: dB rise that triggers capture
ed.WindowLength = 300;             % <- set: integration window [0, 4095]

% Optional: visualize energy curves before capturing (TX must be running for transmit-then-detect)
% plotDetectionSignals(ed, milliseconds(2));

% Capture data upon detection
[data, timestamp, droppedSamples, status] = capture(ed, milliseconds(5), seconds(2));

%% Verify
if status == 1
    r = max(abs(data).^2) / median(abs(data).^2);   % sanity ratio: real signal r >= 50
    fprintf("Captured %d samples at %s (dropped: %d). Sanity ratio r = %.1f (>= 50 = real signal).\n", ...
        numel(data), string(timestamp), droppedSamples, r);
    if r < 50
        warning("Sanity ratio below 50 - this looks like noise, not signal; see references/threshold-calibration.md.");
    end
else
    warning("No detection before timeout (status 0) - expected with no active signal; to tune see references/threshold-calibration.md.");
end

%% Energy Detection - Fixed Threshold
% Detect and capture signal when energy exceeds fixed level.
clear ed pd
radioName = "TestX410";            % <- set: your radio configuration name
ed = energyDetector(radioName);

% Configure RF parameters
ed.CenterFrequency = 3.5e9;        % <- set: Hz
ed.SampleRate = 122.88e6;          % <- set: Hz
ed.RadioGain = 30;                 % <- set: dB (device-dependent range)
ed.CaptureDataType = "double";

% Configure fixed threshold
ed.ThresholdMethod = "fixed";
ed.FixedThreshold = 500;           % <- set: fixed power threshold [0, 8191]; over loopback, measure it (see Loopback) — 500 is an OTA placeholder
ed.WindowLength = 300;             % <- set: integration window [0, 4095]

% Capture data upon detection
[data, timestamp, droppedSamples, status] = capture(ed, milliseconds(1), seconds(1));

%% Verify
if status == 1
    r = max(abs(data).^2) / median(abs(data).^2);   % sanity ratio: real signal r >= 50
    fprintf("Captured %d samples at %s (dropped: %d). Sanity ratio r = %.1f (>= 50 = real signal).\n", ...
        numel(data), string(timestamp), droppedSamples, r);
    if r < 50
        warning("Sanity ratio below 50 - this looks like noise, not signal; see references/threshold-calibration.md.");
    end
else
    warning("No detection before timeout (status 0) - signal did not exceed the fixed threshold; measure it (see references/threshold-calibration.md).");
end

%% Preamble Detection - Adaptive Threshold
% Detect and capture signal by correlating with known preamble.
clear ed pd
radioName = "SigRadio";            % <- set: your radio configuration name
pd = preambleDetector(radioName);

% Configure RF parameters
pd.CenterFrequency = 2.2e9;        % <- set: Hz
pd.SampleRate = 10.24e6;           % <- set: Hz
pd.RadioGain = 30;                 % <- set: dB (device-dependent range)
pd.CaptureDataType = "double";

% Define preamble sequence (e.g., normalized Zadoff-Chu)
seq = zadoffChuSeq(38, 137);       % <- set: root index, sequence length [4, 1024]
preamble = seq / norm(seq, 2);
pd.Preamble = preamble;

% Configure adaptive threshold
pd.ThresholdMethod = "adaptive";
pd.AdaptiveThresholdGain = 0.3;    % <- set: typical 4-16 OTA, 0.1-0.9 loopback (boundary at 1.0)
pd.AdaptiveThresholdOffset = 0.001; % <- set: start at 0; raise only if false triggers occur

% Optional: visualize threshold curve before capturing (TX must be running)
% plotThreshold(pd, milliseconds(1));

% Capture data upon preamble detection
[data, timestamp, droppedSamples, status] = capture(pd, milliseconds(10), seconds(1));

%% Verify
if status == 1
    matched = filter(conj(flipud(pd.Preamble)), 1, data);
    r = max(abs(matched).^2) / median(abs(matched).^2);   % real preamble fire: r > 100
    fprintf("Captured %d samples at %s (dropped: %d). Sanity ratio r = %.1f (> 100 = real preamble).\n", ...
        numel(data), string(timestamp), droppedSamples, r);
    if r < 100
        warning("Sanity ratio below 100 - marginal, or fired on noise instead of the preamble; see references/threshold-calibration.md.");
    end
else
    warning("No detection before timeout (status 0) - preamble not correlated; to tune see references/threshold-calibration.md.");
end

%% Preamble Detection - Fixed Threshold
% Detect preamble using fixed correlation power threshold.
clear ed pd
radioName = "MyX310";              % <- set: your radio configuration name
pd = preambleDetector(radioName);

% Configure RF parameters
pd.CenterFrequency = 2.4e9;        % <- set: Hz
pd.SampleRate = 30.72e6;           % <- set: Hz
pd.RadioGain = 30;                 % <- set: dB (device-dependent range)
pd.CaptureDataType = "double";

% Define preamble sequence
seq = zadoffChuSeq(25, 63);        % <- set: root index, sequence length [4, 1024]
preamble = seq / norm(seq, 2);
pd.Preamble = preamble;

% Configure fixed threshold
pd.ThresholdMethod = "fixed";
pd.FixedThreshold = 0.1;           % <- set: fixed correlation threshold [0, 4095]

% Plot threshold to calibrate (this pattern's purpose)
plotThreshold(pd, milliseconds(1));

% Capture data upon preamble detection
[data, timestamp, droppedSamples, status] = capture(pd, milliseconds(10), seconds(1));

%% Verify
if status == 1
    matched = filter(conj(flipud(pd.Preamble)), 1, data);
    r = max(abs(matched).^2) / median(abs(matched).^2);   % real preamble fire: r > 100
    fprintf("Captured %d samples at %s (dropped: %d). Sanity ratio r = %.1f (> 100 = real preamble).\n", ...
        numel(data), string(timestamp), droppedSamples, r);
    if r < 100
        warning("Sanity ratio below 100 - marginal, or fired on noise instead of the preamble; see references/threshold-calibration.md.");
    end
else
    warning("No detection before timeout (status 0) - preamble not above the fixed threshold; to tune see references/threshold-calibration.md.");
end

%% Multi-Capture Energy Detection
% Capture multiple consecutive signals with sample clock timestamps.
% The "NumCaptures" name-value requires R2023b + R2024a or later (single capture works on R2023b).
clear ed pd
radioName = "MultiCap";            % <- set: your radio configuration name
ed = energyDetector(radioName, ...
    CaptureDataType="double", ...
    TimestampUnit="sample-clock-cycle");

% Configure RF parameters
ed.CenterFrequency = 3.5e9;        % <- set: Hz
ed.SampleRate = 245.76e6;          % <- set: Hz
ed.RadioGain = 30;                 % <- set: dB (device-dependent range)

% Configure threshold
ed.ThresholdMethod = "adaptive";
ed.MinimumEnergy = 0.1;            % <- set: energy floor [0, 8191]; use 0 over loopback (let the dB delta trigger)
ed.EnergyDeltaThreshold = 3;       % <- set: dB rise that triggers capture

% Capture N consecutive signals
numCaptures = 5;                   % <- set: number of consecutive captures (R2024a+)
[data, timestamp, droppedSamples, status] = capture(ed, ...
    milliseconds(1), seconds(3), "NumCaptures", numCaptures);

%% Verify
if status > 0
    if iscell(data)                % NumCaptures > 1 returns a cell array, one cell per capture
        firstCapture = data{1};
    else
        firstCapture = data;
    end
    r = max(abs(firstCapture).^2) / median(abs(firstCapture).^2);   % real signal r >= 50
    fprintf("Successfully captured %d of %d requested signals (%d samples each).\n", ...
        status, numCaptures, numel(firstCapture));
    fprintf("Capture 1 sanity ratio r = %.1f (>= 50 = real signal).\n", r);
    fprintf("Timestamps (clock cycles): %s\n", mat2str(timestamp));
    if r < 50
        warning("Sanity ratio below 50 - this looks like noise, not signal; see references/threshold-calibration.md.");
    end
else
    warning("No signals captured before timeout - expected with no active signal; to tune see references/threshold-calibration.md.");
end

%% Transmit and Detect with Energy Detector
% Transmit a test waveform and capture upon energy detection.
clear ed pd
radioName = "TestN310";            % <- set: your radio configuration name
ed = energyDetector(radioName);

% Configure RF parameters
ed.CenterFrequency = 2.45e9;       % <- set: Hz
ed.SampleRate = 30.72e6;           % <- set: Hz
ed.Antennas = "RF0:RX2";  % loopback partner of RF0:TX/RX
ed.RadioGain = 30;                 % <- set: dB (typical 20-40 OTA, ~30 loopback)
ed.CaptureDataType = "double";

% Configure adaptive threshold
ed.ThresholdMethod = "adaptive";
ed.MinimumEnergy = 0;              % <- loopback: 0 lets the dB delta trigger (scale-invariant); see Loopback
ed.EnergyDeltaThreshold = 1.5;     % <- dB rise; loopback rise scales with TransmitGain: ~1.5 at TxGain 30, ~3 at 50 (see Loopback)

% Generate test waveform (chirp with zero padding) — keep it complex ('complex') and column-shaped for transmit
chirpSignal = single(chirp(0:1/1e3:2, 0, 0.5, 15, 'complex')).';
chirpSignal(end) = [];
padLen = 6500;
zeroPad = complex(zeros(padLen, 1), zeros(padLen, 1));
testWaveform = [zeroPad; chirpSignal * 0.999; zeroPad];

% Transmit test waveform continuously
transmit(ed, testWaveform, "continuous", ...
    TransmitAntennas="RF0:TX/RX", ...
    TransmitGain=50);  % <- set: typical 10-30 dB OTA, ~50 dB loopback

% Capture upon energy detection
[data, timestamp, droppedSamples, status] = capture(ed, milliseconds(3), seconds(2));

% Stop transmission
stopTransmission(ed);

%% Verify
if status == 1
    % A chirp is wideband, so the raw ratio under-reports: r ~15-20 is normal here.
    % The matched filter against the known TX waveform is the authoritative check.
    r = max(abs(data).^2) / median(abs(data).^2);
    template = double(chirpSignal) / norm(double(chirpSignal));
    mf = abs(filter(conj(flipud(template)), 1, data));
    mfRatio = max(mf).^2 / median(mf).^2;
    fprintf("Captured %d samples of test waveform (dropped: %d). Transmission stopped.\n", ...
        numel(data), droppedSamples);
    fprintf("Raw ratio r = %.1f (15-20 is normal for a chirp); matched-filter ratio = %.1f (>> 100 = real signal).\n", ...
        r, mfRatio);
    if mfRatio < 100
        warning("Matched-filter ratio below 100 - the capture may be noise; see references/threshold-calibration.md.");
    end
else
    warning("No detection before timeout (status 0) - raise TransmitGain/RadioGain or set MinimumEnergy=0; see references/threshold-calibration.md.");
end

%% WLAN Channel Scan with Preamble Detection
% Scan multiple WLAN channels for activity using preamble detection.
clear ed pd
radioName = "WiFiScanner";         % <- set: your radio configuration name
pd = preambleDetector(radioName);

% Configure preamble detector
pd.CaptureDataType = "double";
pd.ThresholdMethod = "adaptive";
pd.AdaptiveThresholdGain = 0.3;    % <- set: typical 4-16 OTA, 0.1-0.9 loopback
pd.AdaptiveThresholdOffset = 0.001; % <- set: start at 0; raise if false triggers occur
pd.RadioGain = 30;                 % <- set: dB (device-dependent range)

% Define WLAN L-LTF preamble (legacy long training field)
% wlanNonHTConfig defaults to CBW20, so wlanLLTF returns 160 samples at 20 MHz.
lltf = wlanLLTF(wlanNonHTConfig);
preamble = lltf / max(abs(lltf));  % raw max|L-LTF| is ~1.44 - must scale into [-1, 1]
pd.Preamble = preamble;

% Define channels to scan (e.g., 2.4 GHz band channels 1, 6, 11)
channelFreqs = [2.412e9, 2.437e9, 2.462e9];
channelNames = ["Ch1", "Ch6", "Ch11"];
% SampleRate MUST match the preamble's own rate, or the correlator never peaks.
% CBW20 L-LTF is sampled at 20 MHz. Change the bandwidth and change this together.
sampleRate = 20e6;                 % <- set: Hz (must equal the L-LTF bandwidth)
pd.SampleRate = sampleRate;

% Scan each channel
captures = struct([]);
for idx = 1:length(channelFreqs)
    pd.CenterFrequency = channelFreqs(idx);
    [data, timestamp, ~, detectionOk] = capture(pd, ...
        milliseconds(10), milliseconds(100));
    if detectionOk
        captures = [captures, struct( ...
            Channel=channelNames(idx), ...
            Frequency=channelFreqs(idx), ...
            Data=data, ...
            Timestamp=timestamp)]; %#ok<AGROW>
    end
end

%% Verify
fprintf("Scan complete. Detected activity on %d of %d channels.\n", ...
    numel(captures), numel(channelFreqs));
if isempty(captures)
    warning("No activity on any channel - first confirm SampleRate matches the preamble bandwidth (20 MHz for CBW20 L-LTF), then tune AdaptiveThresholdGain; see references/threshold-calibration.md.");
else
    for k = 1:numel(captures)
        matched = filter(conj(flipud(pd.Preamble)), 1, captures(k).Data);
        r = max(abs(matched).^2) / median(abs(matched).^2);   % real preamble fire: r > 100
        fprintf("  %s (%.3f GHz): %d samples, sanity ratio r = %.1f (> 100 = real preamble)\n", ...
            captures(k).Channel, captures(k).Frequency/1e9, numel(captures(k).Data), r);
        if r < 100
            warning("%s ratio below 100 - marginal, or fired on noise instead of the preamble; see references/threshold-calibration.md.", captures(k).Channel);
        end
    end
end