9ce23c4a10
new general processing structure just before splitting off the projects folder from this repo
80 lines
2.6 KiB
Matlab
80 lines
2.6 KiB
Matlab
function [std_total,std_lvl] = calc_std(test_signal,reference_signal,options)
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arguments(Input)
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test_signal;
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reference_signal;
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options.skip_front = 0;
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options.skip_end = 0;
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options.returnErrorLocation = 0;
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end
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options.skip_end = abs(options.skip_end);
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options.skip_front = abs(options.skip_front);
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assert((options.skip_end+options.skip_front)<length(test_signal),"You can not skip more bits than overall length of data! Set skip_front or skip_end to lower value or check data_in");
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if isa(reference_signal,'Signal')
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reference_signal = reference_signal.signal;
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end
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if isa(test_signal,'Signal')
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test_signal = test_signal.signal;
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end
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% TRIM
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[test_signal,reference_signal]=trimseq(test_signal,reference_signal,options.skip_front,options.skip_end);
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% CALC EVM
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[std_total, std_lvl, nsd_lvl, d_min]= calc_std_(test_signal,reference_signal);
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std_lvl = nsd_lvl;
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function [std_total, std_lvl, nsd_lvl, d_min] = calc_std_(test_signal, reference_signal)
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% NSD (Normalized Standard Deviation) expresses the noise spread at each symbol level
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% relative to the minimum distance between levels. A low NSD means low error risk,
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% while NSD approaching 0.5 indicates a high chance of symbol errors due to noise.
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% Ensure input is column vector
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test_signal = test_signal(:);
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reference_signal = reference_signal(:);
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assert(length(test_signal) == length(reference_signal), "Sequence length does not match");
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% Find unique levels and their minimum spacing
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k = unique(reference_signal);
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d_min = min(diff(k)); % Minimum distance between adjacent levels
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% Normalize test signal to RMS=1 (if not already)
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test_signal = test_signal / rms(test_signal);
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% Overall standard deviation (not normalized)
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std_total = std(test_signal);
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% Per-level standard deviation and normalized std
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std_lvl = zeros(1, length(k));
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nsd_lvl = zeros(1, length(k));
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for lvl = 1:length(k)
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idx = reference_signal == k(lvl);
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if any(idx)
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std_lvl(lvl) = std(test_signal(idx));
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nsd_lvl(lvl) = std_lvl(lvl) / d_min;
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else
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std_lvl(lvl) = NaN;
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nsd_lvl(lvl) = NaN;
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end
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end
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end
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function [data_,reference_] = trimseq(data,reference,skipstart,skip_end)
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data_ = data(skipstart+1:end-skip_end,:);
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delta_bits = length(reference) - length(data);
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skip_end = delta_bits + skip_end;
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reference_ = reference(skipstart+1:end-skip_end,:);
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end
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end |