4099f6820f
WDM code added (Pol Cont., Opt MUX/DEMUX, Opt Atten, DP_Fiber) -> the codebase is not optimized to always work with dp signals!
79 lines
2.1 KiB
Matlab
79 lines
2.1 KiB
Matlab
M = 6;
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data = [1,2,3,4,5,6];
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M = 6;
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bitpattern = [];
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s = RandStream('twister','Seed',1);
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for i = 1:log2(M)
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N = 2^(12-1); %length of prbs
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bitpattern(:,i) = randi(s,[0 1], N, 1);
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end
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if M == 6
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bitpattern = reshape(bitpattern',[],1);
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bitpattern = bitpattern(1:end-mod(length(bitpattern),5));
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end
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bits = Informationsignal(bitpattern);
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symbols = PAMmapper(M,0).map(bits);
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symbols_tx_prec = Duobinary().precode(symbols);
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% all possible transitions (for now 36, including the "edges"
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% of the QAM 32 constellation)
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states = PAMmapper(6,0,"eth_style",0).levels;
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pam6transitions = combvec(states,states)'; % pam6transitions =
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% [-5 -5;
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% -3 -5;
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% -1 -5; ...
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pam6transitions_serial = reshape(pam6transitions',[],1);
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data = pam6transitions_serial;
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data = round(data);
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b = min(data);
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data = data - b;
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data = data ./ 2;
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% THIS WAS USED!
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bk = zeros(size(data));
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for k = 2:numel(data)
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bk(k) = mod(data(k)-bk(k-1),M);
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end
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%% State Analysis
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x = bk;%symbols_tx_prec.signal;
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levels = sort(unique(x)).'; % or provide known 1x6 level values
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[~,ix] = min(abs(x - levels),[],2);
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x = levels(ix); % snapped/quantized
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%% TRANSITION COUNTS & PROBABILITIES
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K = numel(levels);
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% map to state indices 1..K
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[tf, idx] = ismember(x, levels);
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idx = idx(:);
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from = idx(1:end-1);
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to = idx(2:end);
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from = idx(1:2:end);
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to = idx(2:2:end);
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% counts C(from,to)
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C = accumarray([from,to], 1, [K K], @sum, 0);
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% row-stochastic transition matrix P(to|from)
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rowSums = sum(C,2);
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P = C ./ max(rowSums,1);
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%% 1) HEATMAP (which transitions are more probable?)
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figure('Name','Transition Probabilities (to | from)');
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h = heatmap(levels, levels, P, 'Colormap', parula, 'ColorbarVisible','on');
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colormap(gca,[[1,1,1];flip(cbrewer2('Spectral',100))]);clim([0,ceil(max(P(:))*10)/10]);
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h.XLabel = 'From state (level)';
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h.YLabel = 'To state (level)';
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h.Title = 'P(to | from)';
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%% 2) WEIGHTED TRANSITION GRAPH
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% Use dtmc if you have Econometrics Toolbox:
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mc = dtmc(P, 'StateNames', string(levels));
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figure('Name','Markov Graph (dtmc)');
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gp = graphplot(mc, 'ColorEdges',true, 'LabelEdges',true); |