Files
2026-05-24 21:10:00 +02:00

106 lines
3.4 KiB
Matlab

calculations_only = false;
window = 512;
overlap = 64;
fft_precision = 2048;
sample_rate = 20e6; % 20 MS/s -> 20e6 S/s
channels = [1 5 9 13];
res1 = analyzeTrace("traces/2412mhz.mat", channels(1), window, overlap, fft_precision, sample_rate);
res2 = analyzeTrace("traces/2432mhz.mat", channels(2), window, overlap, fft_precision, sample_rate);
res3 = analyzeTrace("traces/2452mhz.mat", channels(3), window, overlap, fft_precision, sample_rate);
res4 = analyzeTrace("traces/2472mhz.mat", channels(4), window, overlap, fft_precision, sample_rate);
results = [res1 res2 res3 res4];
% Calibrated color scale over all traces
all_P_dB = [
res1.P_dB(:)
res2.P_dB(:)
res3.P_dB(:)
res4.P_dB(:)
];
p_dB_min = min(all_P_dB);
p_dB_max = max(all_P_dB);
% 2
if ~calculations_only
plotSpectrogram(res1, 1, p_dB_min, p_dB_max);
plotSpectrogram(res2, 2, p_dB_min, p_dB_max);
plotSpectrogram(res3, 3, p_dB_min, p_dB_max);
plotSpectrogram(res4, 4, p_dB_min, p_dB_max);
end
%{
% 3.
% taking the 10th percentile on the linear values or the logarithmic ones
% should not make any difference
noise_floor1_linear = prctile(mag1(:), 10);
noise_floor2_linear = prctile(mag2(:), 10);
noise_floor3_linear = prctile(mag3(:), 10);
noise_floor4_linear = prctile(mag4(:), 10);
noise_floor1 = linearTodB(noise_floor1_linear);
noise_floor2 = linearTodB(noise_floor2_linear);
noise_floor3 = linearTodB(noise_floor3_linear);
noise_floor4 = linearTodB(noise_floor4_linear);
% this is false -> linear avg on logarithmic values
% noise_floor_avg = sum([noise_floor1 noise_floor2, noise_floor3, noise_floor4]) / 4;
noise_floor_avg = linearTodB(mean([noise_floor1_linear noise_floor2_linear noise_floor3_linear noise_floor4_linear]));
% 4.
occupancy1 = sum(P1_dB(:) > noise_floor1 + 10) / numel(P1_dB) * 100;
occupancy2 = sum(P2_dB(:) > noise_floor2 + 10) / numel(P2_dB) * 100;
occupancy3 = sum(P3_dB(:) > noise_floor3 + 10) / numel(P3_dB) * 100;
occupancy4 = sum(P4_dB(:) > noise_floor4 + 10) / numel(P4_dB) * 100;
%}
% 3.
% Sum all frequency bins per time slot to obtain total channel power.
noise_floor_avg = linearTodB(mean([
res1.noise_floor_linear
res2.noise_floor_linear
res3.noise_floor_linear
res4.noise_floor_linear
]));
% 4.
occupancies = [res1.occupancy res2.occupancy res3.occupancy res4.occupancy];
[occupancy_max, max_idx] = max(occupancies);
busiest_channel = channels(max_idx);
if ~calculations_only
disp("Results Task 1:" + newline)
disp("-- Trace duration ---")
disp("Channel 1 duration: " + res1.duration + "s")
disp("Channel 5 duration: " + res2.duration + "s")
disp("Channel 9 duration: " + res3.duration + "s")
disp("Channel 13 duration: " + res4.duration + "s" + newline)
disp("--- Noise floor ---")
disp("Distinct:")
disp("Channel 1 noise floor: " + res1.noise_floor + "dB")
disp("Channel 5 noise floor: " + res2.noise_floor + "dB")
disp("Channel 9 noise floor: " + res3.noise_floor + "dB")
disp("Channel 13 noise floor: " + res4.noise_floor + "dB" + newline)
disp("Combined:")
disp("Channel all noise floor: " + noise_floor_avg + "dB" + newline)
disp("-- Occupancy ---")
disp("Channel 1 occupancy: " + res1.occupancy + "%")
disp("Channel 5 occupancy: " + res2.occupancy + "%")
disp("Channel 9 occupancy: " + res3.occupancy + "%")
disp("Channel 13 occupancy: " + res4.occupancy + "%" + newline)
disp("Busiest channel: " + busiest_channel + newline)
end