PR filter viz
Zürich data Refactoring/ Organization
This commit is contained in:
Silas Oettinghaus
@@ -17,7 +17,7 @@
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%% Fiber and wavelength parameters
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lambda0 = 1310e-9; % Zero-dispersion wavelength (ZDW) [m]
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S0 = 0.08; % Dispersion slope at ZDW [ps/(nm^2·km)]
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L = 10000; % Fiber length [m]
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L = 8000; % Fiber length [m]
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alpha_dB = 0; % Attenuation [dB/m] (ignored here)
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%% Target null frequency
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50
Theory/Optical/Dispersion/power_fading.m
Normal file
50
Theory/Optical/Dispersion/power_fading.m
Normal file
@@ -0,0 +1,50 @@
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%% ============================================================
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% Minimal IM/DD Power Fading Plot
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% ============================================================
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%% Fiber and system parameters
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lambda0 = 1309e-9; % zero-dispersion wavelength [m]
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lambda = 1370e-9; % operating wavelength [m]
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S0 = 0.092; % dispersion slope [ps/(nm²·km)]
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L = 30e3; % fiber length [m]
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c = physconst('lightspeed');
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%% Derived quantities
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S0_si = S0 * 1e3; % → s/m³
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D_lambda = (S0/4) * (lambda*1e9 - (lambda0*1e9)^4/(lambda*1e9)^3); % ps/(nm·km)
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D_si = D_lambda * 1e-6; % → s/m²
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b2 = -D_si * lambda^2 / (2*pi*c); % s²/m
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Dacc = D_lambda * L;
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fprintf('Accumulated Dispersion: %.2f ps/nm \n', Dacc / 1e3);
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%% Frequency grid
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f_max = 200e9;
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f = linspace(0, f_max, 5000); % [Hz]
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%% IM/DD transfer function (power fading)
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phi = 2*pi^2 * b2 * f.^2 * L;
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H = abs(cos(phi));
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%% Plot
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figure('Color','w');
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plot(f/1e9, 10*log10(H), 'LineWidth', 1,'Color','black');
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grid on; box on;
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xlabel('Frequency [GHz]');
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ylabel('Magnitude [dB]');
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% title(sprintf('IM/DD Power Fading: 10 km; 1275nm', lambda*1e9, L/1000),"Interpreter","latex");
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ylim([-20 0]);
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%% Mark analytic null frequencies up to order 5
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max_order = 3;
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for n = 0:max_order
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f_null_n = sqrt( c*(2*n + 1)/(2*abs(D_si)*lambda^2*L) );
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xline(f_null_n/1e9, '--', 'LineWidth', 1.2, ...
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'Color', [0.1216, 0.4706, 0.7059]);
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text(f_null_n/1e9, -15, sprintf('$f_{\\mathrm{null}, %d}=%.1f$ GHz', n, f_null_n/1e9), ...
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'BackgroundColor', 'w', 'EdgeColor', 'k', 'Interpreter', 'latex', ...
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'HorizontalAlignment', 'center', 'VerticalAlignment', 'middle');
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end
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% mat2tikz_improved('C:\Users\Silas\Documents\6971e0b65b380ca6d71c837f\02_IMDD_System\tikz\dispersion\power_fading.tikz')
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100
Theory/Signal_Processing/partial_response_filter.m
Normal file
100
Theory/Signal_Processing/partial_response_filter.m
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@@ -0,0 +1,100 @@
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% DUOBINARY CLASSES
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% Define the filter taps
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h_ = {1,[1 1],[1 2 1],[1 3 3 1]};
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desc = {'$1$','$(1+D)$','$(1+D)^2$','$(1+D)^3$'};
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for i = 1:length(h_)
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h = h_{i};
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[H, w] = freqz(h, 1, 1024, 1);
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figure(1);
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hold on
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plot(w, 10*log10(abs(H)), 'LineWidth', 1, 'DisplayName',desc{i}); %todo
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xlabel('Normalized Frequency');
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ylabel('Amplitude in dB');
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grid on;
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ylim([-20,10]);
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end
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legend
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beautifyBERplot("logscale",false,"setmarkers",false);
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% mat2tikz_improved("C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/03_DSP_Techniques/tikz/duobinary_response.tikz")
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%%
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% 1+ alpha D
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% Define the filter taps
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h_ = {[1, 0],[1 0.2],[1 0.4],[1 0.6],[1 0.8],[1 1]};
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for i = 1:length(h_)
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h = h_{i};
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[H, w] = freqz(h, 1, 1024, 1);
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figure(2);
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hold on
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plot(w, 10*log10(abs(H)), 'LineWidth', 2,'DisplayName',sprintf('$\\alpha = %.1f$', h(end))); %todo
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xlabel('Normalized Frequency');
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ylabel('Amplitude in dB');
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grid on;
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ylim([-15,5])
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end
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legend
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beautifyBERplot("logscale",false,"setmarkers",false);
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% mat2tikz_improved("C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/03_DSP_Techniques/tikz/partial_response.tikz")
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%%
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useprbs = 0;
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M = 4;
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randkey = 2;
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fsym = 112e9;
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%%%%% PRBS Generation in correct shape for Modulation Format %%%%%%
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O = 19; %order of prbs
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N = 2^(O-1); %length of prbs
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[~,seed] = prbs(O,1); %initialize first seed of prbs
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bitpattern=[];
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if useprbs
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for i = 1:log2(M)
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[bitpattern(:,i),seed] = prbs(O,N,seed);
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end
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else
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s = RandStream('twister','Seed',randkey);
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for i = 1:log2(M)
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bitpattern(:,i) = randi(s,[0 1], N, 1);
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end
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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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Tx_bits = Informationsignal(bitpattern);
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Digi_Mod = PAMmapper(M,0);
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Symbols_tx = Digi_Mod.map(Tx_bits);
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Symbols_tx.fs = fsym;
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cnt = 1;
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Symbols = Symbols_tx;
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Symbols = Duobinary().precode(Symbols);
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Symbols = Duobinary().encode(Symbols);
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figure()
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histogram()
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% Symbols = Duobinary().decode(Symbols);
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% coeff = [1,0.5];
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%
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% Symbols.signal = filter(coeff, 1, Symbols.signal);
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% Symbols.spectrum("fignum",2,"displayname",['coeff:',num2str(coeff)],"normalizeTo0dB",1);
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