PR and DB fummelei

Theory/Mapping_Coding/partial_response/duobinary_emulation_minimal_example.m

@@ -3,22 +3,12 @@
 M = 4;
 apply_precode = 1;
 
-bitpattern = [];
+bits = Signalgenerator( ...
-s = RandStream('twister','Seed',1);
+        "form", signalform.prms, ...
-for i = 1:log2(M)
+        "M", M, ...
-    N = 2^(17-1); %length of prbs
+        "order", 15).process();
-    bitpattern(:,i) = randi(s,[0 1], N, 1);
-end
-
-if M == 6
-    bitpattern = reshape(bitpattern',[],1);
-    bitpattern = bitpattern(1:end-mod(length(bitpattern),5));
-end
-
-bits = Informationsignal(bitpattern);
 
 symbols = PAMmapper(M,0).map(bits);
-
 bits_rx = PAMmapper(M,0).demap(symbols);
 [~,~,ber_direct,~] = calc_ber(bits.signal,bits_rx.signal,"skip_front",0,"skip_end",0,"returnErrorLocation",1);
 
@@ -27,10 +17,6 @@ if apply_precode
 else
     symbols_tx = symbols;
 end
-disp(['Tx Sequenz: -- RMS:',sprintf('%.1f',rms(symbols_rx.signal)),' - - Levels -',num2str(numel(unique(symbols_rx.signal)))]);
-unique(symbols_tx.signal)
-disp('- - - - - - - - - -');
-
 
 show2Dconstellation(symbols_tx,symbols_tx,"displayname",'VNLE Out','fignum',2241);
     
@@ -62,7 +48,7 @@ disp(['BER: ',sprintf('%.1E',ber),' - - PAM-',num2str(M)]);
 
 figure()
 subplot(1,2,1)
-histogram(symbols_tx.signal,100,'Normalization','count')
+histogram(symbols_tx.signal,100,'Normalization','probability')
 
 subplot(1,2,2)
-histogram(symbols_db.signal,100,'Normalization','count')
+histogram(symbols_db.signal,100,'Normalization','probability')

Theory/Mapping_Coding/partial_response/duobinary_minimal_example.m

@@ -4,46 +4,10 @@ randkey = 1;
 datarate = 448e9;
 fsym = round(datarate / log2(M)) ;
 
-%%%%% PRBS Generation in correct shape for Modulation Format %%%%%%
+Tx_bits = Signalgenerator( ...
-O = 16; %O of prbs
+        "form", signalform.prms, ...
-N = 2^(O); %length of prbs
+        "M", M, ...
-[~,seed] = prbs(O,1); %initialize first seed of prbs
+        "order", 15).process();
-bitpattern=[];
-
-state = struct();
-
-para = struct();
-
-if M == 6
-    para.bl = 2^(O-2);
-    para.dimension = 5;
-else
-    para.bl = 2^(O-1);
-    para.dimension = log2(M); %2.5bits/sym -> 2 bit/sym
-end
-
-para.rand = 0;
-
-para.order = floor(O / log2(M));
-para.skip =0;
-para.bruijn = 0;
-para.reset_prms = 0;
-para.method = 1;
-
-data_in = [];
-global loop;
-loop = 0;
-[data_out,state_] = prms(data_in, state, para);
-loop = 1;
-[data_out,state_out] = prms(data_in, state_, para);
-bitpattern = data_out';
-
-if M == 6
-    bitpattern = reshape(bitpattern',[],1);
-    bitpattern = bitpattern(1:end-mod(length(bitpattern),5));
-end
-
-Tx_bits = Informationsignal(bitpattern);
 
 %%%%% Duobinary %%%%%%
 close all
@@ -96,8 +60,7 @@ for n = 10
 
     Rx_bits = PAMmapper(M,0).demap(Symbols_rx);
     
-    %%%%% Check BER of Bit Sequence %%%%%%
+    %%%%% Check BER of Bit Sequence %%%%%
-    
     [~,error_num(n+1),ber,error_pos] = calc_ber(Tx_bits.signal,Rx_bits.signal,"skip_front",10,"skip_end",10,"returnErrorLocation",1);
     
     % disp(['BER: ',sprintf('%.1E',ber),sprintf(' - Num. Err: %.1d',error_num(n+1)-2),' - - PAM-',num2str(M)]);

Theory/Mapping_Coding/partial_response/pam_6_differential_code_understand.m

@@ -71,9 +71,3 @@ colormap(gca,[[1,1,1];flip(cbrewer2('Spectral',100))]);clim([0,ceil(max(P(:))*10
 h.XLabel = 'From state (level)'; 
 h.YLabel = 'To state (level)';
 h.Title  = 'P(to | from)';
-
-%% 2) WEIGHTED TRANSITION GRAPH
-% Use dtmc if you have Econometrics Toolbox:
-mc = dtmc(P, 'StateNames', string(levels));
-figure('Name','Markov Graph (dtmc)');
-gp = graphplot(mc, 'ColorEdges',true, 'LabelEdges',true);

Theory/Mapping_Coding/partial_response/partial_response_filter.m

@@ -0,0 +1,86 @@
+
+% DUOBINARY CLASSES
+% Define the filter taps
+h_ = {1,[1 1],[1 2 1],[1 3 3 1]};
+desc = {'$1$','$(1+D)$','$(1+D)^2$','$(1+D)^3$'};
+
+for i = 1:length(h_)
+    h = h_{i};
+    
+    [H, w] = freqz(h, 1, 1024, 1);
+    
+    figure(1);
+    hold on
+    plot(w, 10*log10(abs(H)), 'LineWidth', 1, 'DisplayName',desc{i}); %todo
+    xlabel('Normalized Frequency');
+    ylabel('Amplitude in dB');
+    grid on;
+    ylim([-20,10]);
+    
+end
+
+legend
+beautifyBERplot("logscale",false,"setmarkers",false);
+% mat2tikz_improved("C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/03_DSP_Techniques/tikz/duobinary_response.tikz")
+
+%%
+
+% 1+ alpha D 
+% Define the filter taps
+h_ = {[1, 0],[1 0.3],[1 0.6],[1 0.9],[1 1],[1 2 1],[1 3 3 1]};
+col = {[0 0 0],[0.2000,0.6275,0.1725],[0.1216, 0.4706, 0.7059],[0.8902,0.1020,0.1098],...
+    [0.2000,0.6275,0.1725],[0.9333, 0.9451, 0.9490],[0.9333, 0.9451, 0.9490]};
+sty = {':','-','-','-','--','--','--'};
+
+
+for i = 1:length(h_)
+    h = h_{i};
+    
+    [H, w] = freqz(h, 1, 1024, 1);
+    
+    figure(2);
+    hold on
+    dn = sprintf('$(1+ %.1f \\, D)$', h(end));
+    if i == 5
+        dn = sprintf('$(1+D)$', h(end));
+    elseif i == 6
+        dn = sprintf('$(1+D)^2$');
+    elseif i == 7
+        dn = sprintf('$(1+D)^3$');
+    elseif i == 1
+        dn = sprintf('$1$');
+    end
+
+    plot(w, 10*log10(abs(H)), 'LineWidth', 2,'DisplayName',dn,'Color',col{i},'LineStyle',sty{i}); %todo
+    xlabel('Normalized Frequency');
+    ylabel('Amplitude in dB');
+    grid on;
+    ylim([-20,10])
+end
+legend
+beautifyBERplot("logscale",false,"setmarkers",false,"setcolors",false);
+% mat2tikz_improved("C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/03_DSP_Techniques/tikz/partial_response_2.tikz")
+
+%%
+
+useprbs = 0;
+M = 4;
+randkey = 2;
+fsym = 112e9;
+
+Tx_bits = Signalgenerator("form", signalform.prms,"M", M,"order", 17).process();
+Symbols_tx = PAMmapper(M,0).map(Tx_bits);
+Symbols_tx.fs = fsym;
+
+cnt = 1;
+
+Symbols = Symbols_tx;
+
+Symbols = Duobinary().precode(Symbols);
+Symbols = Duobinary().encode(Symbols);
+Symbols = Duobinary().decode(Symbols);
+
+for alpha = 0:0.2:1
+    Symbols.signal = filter([1,alpha], 1, Symbols.signal);
+    Symbols.spectrum("fignum",2,"displayname",['coeff:',num2str(alpha)],"normalizeTo0dB",1,"normalizeToNyquist",0,"normalizeToSamplingRate",1);
+end

Theory/Mapping_Coding/partial_response/test_db_minimal_example.m

@@ -2,19 +2,10 @@
 M = 4;
 apply_precode_at_tx = 1;
 
-bitpattern = [];
+bits = Signalgenerator( ...
-s = RandStream('twister','Seed',1);
+    "form", signalform.prms, ...
-for i = 1:log2(M)
+    "M", M, ...
-    N = 2^(17-1); %length of prbs
+    "order", 15).process();
-    bitpattern(:,i) = randi(s,[0 1], N, 1);
-end
-
-if M == 6
-    bitpattern = reshape(bitpattern',[],1);
-    bitpattern = bitpattern(1:end-mod(length(bitpattern),5));
-end
-
-bits = Informationsignal(bitpattern);
 
 symbols = PAMmapper(M,0).map(bits);
 
@@ -23,12 +14,13 @@ if apply_precode_at_tx
 else
     symbols_tx = symbols;
 end
+
 disp(['Tx Sequenz: -- RMS:',sprintf('%.1f',rms(symbols_tx.signal)),' - - Levels -',num2str(numel(unique(symbols_tx.signal)))]);
 unique(symbols_tx.signal)
 disp('- - - - - - - - - -');
 
 symbols_tx.signal = awgn(symbols_tx.signal,20,"measured",1);
-% show2Dconstellation(symbols_tx,symbols_tx,"displayname",'VNLE Out','fignum',2241);
+show2Dconstellation(symbols_tx,symbols_tx,"displayname",'VNLE Out','fignum',2241);
     
 
 if apply_precode_at_tx

Theory/Signal_Processing/partial_response_filter.m

@@ -1,100 +0,0 @@
-
-% DUOBINARY CLASSES
-% Define the filter taps
-h_ = {1,[1 1],[1 2 1],[1 3 3 1]};
-desc = {'$1$','$(1+D)$','$(1+D)^2$','$(1+D)^3$'};
-
-for i = 1:length(h_)
-    h = h_{i};
-    
-    [H, w] = freqz(h, 1, 1024, 1);
-    
-    figure(1);
-    hold on
-    plot(w, 10*log10(abs(H)), 'LineWidth', 1, 'DisplayName',desc{i}); %todo
-    xlabel('Normalized Frequency');
-    ylabel('Amplitude in dB');
-    grid on;
-    ylim([-20,10]);
-    
-end
-
-legend
-beautifyBERplot("logscale",false,"setmarkers",false);
-% mat2tikz_improved("C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/03_DSP_Techniques/tikz/duobinary_response.tikz")
-
-%%
-
-% 1+ alpha D 
-% Define the filter taps
-h_ = {[1, 0],[1 0.2],[1 0.4],[1 0.6],[1 0.8],[1 1]};
-
-for i = 1:length(h_)
-    h = h_{i};
-    
-    [H, w] = freqz(h, 1, 1024, 1);
-    
-    figure(2);
-    hold on
-    plot(w, 10*log10(abs(H)), 'LineWidth', 2,'DisplayName',sprintf('$\\alpha = %.1f$', h(end))); %todo
-    xlabel('Normalized Frequency');
-    ylabel('Amplitude in dB');
-    grid on;
-    ylim([-15,5])
-end
-legend
-beautifyBERplot("logscale",false,"setmarkers",false);
-% mat2tikz_improved("C:/Users/Silas/Documents/6971e0b65b380ca6d71c837f/03_DSP_Techniques/tikz/partial_response.tikz")
-
-%%
-
-useprbs = 0;
-M = 4;
-randkey = 2;
-fsym = 112e9;
-
-%%%%% PRBS Generation in correct shape for Modulation Format %%%%%%
-O = 19; %order of prbs
-N = 2^(O-1); %length of prbs
-[~,seed] = prbs(O,1); %initialize first seed of prbs
-bitpattern=[];
-
-if useprbs
-    for i = 1:log2(M)
-        [bitpattern(:,i),seed] = prbs(O,N,seed);
-    end
-else
-    s = RandStream('twister','Seed',randkey);
-    for i = 1:log2(M)
-        bitpattern(:,i) = randi(s,[0 1], N, 1);
-    end
-end
-
-if M == 6
-    bitpattern = reshape(bitpattern,[],1);
-    bitpattern = bitpattern(1:end-mod(length(bitpattern),5));
-end
-
-Tx_bits = Informationsignal(bitpattern);
-
-Digi_Mod = PAMmapper(M,0);
-Symbols_tx = Digi_Mod.map(Tx_bits);
-Symbols_tx.fs = fsym;
-
-cnt = 1;
-
-Symbols = Symbols_tx;
-
-Symbols = Duobinary().precode(Symbols);
-Symbols = Duobinary().encode(Symbols);
-
-figure()
-histogram()
-
-% Symbols = Duobinary().decode(Symbols);
-
-
-% coeff = [1,0.5];
-% 
-% Symbols.signal = filter(coeff, 1, Symbols.signal);
-% Symbols.spectrum("fignum",2,"displayname",['coeff:',num2str(coeff)],"normalizeTo0dB",1);