CLEANUP - changes to folder structure

Theory/Mapping_Coding/test_db_minimal_example.m

@@ -0,0 +1,65 @@
+
+M = 4;
+apply_precode_at_tx = 1;
+
+bitpattern = [];
+s = RandStream('twister','Seed',1);
+for i = 1:log2(M)
+    N = 2^(17-1); %length of prbs
+    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);
+
+if apply_precode_at_tx
+    symbols_tx = Duobinary().precode(symbols);
+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);
+    
+
+if apply_precode_at_tx
+    % Entschiedene Symbole codieren: d_DB(n) = d(n) + d(n-1)    (im Fall von PAM4 7 level [0 1 2 3 4 5 6])
+    symbols_db = Duobinary().encode(symbols_tx);
+
+    disp(['DB encoded -- RMS:',sprintf('%.1f',rms(symbols_db.signal)),' - - Levels -',num2str(numel(unique(symbols_db.signal)))]);
+    unique(symbols_db.signal)
+    disp('- - - - - - - - - -');
+    
+    % Entschiedene codierte Symbole decodieren: d_dec(n) = d_DB(n) mod4
+    symbols_rx = Duobinary().decode(symbols_db);
+else
+    symbols_db = Duobinary().encode(symbols_tx);
+    symbols_rx = Duobinary().decode(symbols_db);
+end
+
+% Vergleichen von b(n) und d_dec(n)
+bits_rx = PAMmapper(M,0).demap(symbols_rx);
+disp(['Wieder normal -- RMS:',sprintf('%.1f',rms(symbols_rx.signal)),' - - Levels -',num2str(numel(unique(symbols_rx.signal)))]);
+unique(symbols_rx.signal)
+disp('- - - - - - - - - -');
+
+
+[~,~,ber,~] = calc_ber(bits.signal,bits_rx.signal,"skip_front",10,"skip_end",10,"returnErrorLocation",1);
+
+disp(['BER: ',sprintf('%.1E',ber),' - - PAM-',num2str(M)]);
+
+figure()
+subplot(1,2,1)
+histogram(symbols_tx.signal,100,'Normalization','count')
+
+subplot(1,2,2)
+histogram(symbols_db.signal,100,'Normalization','count')