src code

Readme.txt

+main函数里有CCDF各曲线需要的函数
+其中average为对称均匀算法的函数，cubic为重写的正交非均匀算法的函数
+
+运行main后（根据需要做的不同曲线，换注解），用paprdecrease.m来做第一篇论文的CCDF曲线（可能需要在main中把对应的方法注解去掉，比如预编码、SCFDE、T-OFDM），第二篇论文的CCDF曲线为cubicPAPR.m
+
+其中整理好的画CCDF曲线的函数为testsemilogy1.m和testsemilogy2.m（必须运行完main中对应的一些函数才能画CCDF），前者为第一篇论文，后者为第二篇论文。
+
+BER部分：
+process.m
+process_ber.m
+BerPlot.m 
+BerOFDM.m
+
+testfunction.m
+
+例子
+clear
+[index,ber] = BerPlot(20,'cubic');
+[index,ber] = BerPlot(20,'average');
+[index,ber] = BerPlot(20,'cubic');
+[index,ber] = BerPlot(20,'average');
+[index,ber] = BerPlot(20,'cubic');
+[index,ber] = BerPlot(20,'average');
+[i,y] = BerOFDM(20);
+[index,ber] = BerPlot(20,'cubic_delta');
+[index,ber] = BerPlot(30,'cubic');
+[index,ber] = BerPlot(30,'average');
+[index,ber] = BerPlot(30,'cubic');
+[index1,ber1] = BerPlot(30,'average');
+[i,y] = BerOFDM(30);
+testfunction
+x_cubic=linspace(min(index),max(index));
+y_cubic=interp1(index,ber,x_cubic,'cubic');
+semilogy(x_cubic,y_cubic);
+testfunction
+clear
+[index_average,ber_acerage] = BerPlot(30,'average');
+[index_cubic,ber_cubic] = BerPlot(30,'cubic');
+[index_ofdm,ber_ofdm] = BerOFDM(30);
+sqrt(3)
+clear
+[index_average,ber_average] = BerPlot(30,'average');
+[index_cubic,ber_cubic] = BerPlot(30,'cubic');
+[index_ofdm,ber_ofdm] = BerOFDM(30);
+[index_average,ber_average] = BerPlot(30,'average');
+[index_cubic,ber_cubic] = BerPlot(30,'cubic');
+[index_average,ber_average] = BerPlot(30,'average');
+[index_cubic,ber_cubic] = BerPlot(30,'cubic');
+[index_ofdm,ber_ofdm] = BerOFDM(30);
+
+柱状图相关：stemplot.m、dbplot.m和peak.m三个文件，无需main
+直接运行stemplot.m即可出OFDM基本stem图
+换不同的柱状图，按照dbplot.m内的注释说明修改。
+不同的柱状图，可能需要更换x轴和y轴范围，在stemplot.m内修改
+
+另外，CCDF曲线的第三支路信号经常会出现少值的情况，要加大样本，而且可能需要跑许多次才能出满意结果。这里给出了论文的数据结果，如文件夹“matlab数据”所示
\ No newline at end of file

dbplot.m

@@ -12,11 +12,11 @@ function y=dbplot()
 %     end
 
 %% OFDM
-%     for n=1:leng
-%         xo=ofdm_signal();
-%         xoA=abs(xo);
-%         p(n)=10*log10(max(xoA).^2/(mean(xoA.^2)));%ԭʼOFDMźxPAPR
-%     end
+    for n=1:leng
+        xo=ofdm_signal();
+        xoA=abs(xo);
+        p(n)=10*log10(max(xoA).^2/(mean(xoA.^2)));%原始OFDM信号x的PAPR
+    end
 
 %% T-OFDM
 %     for n=1:leng
@@ -32,14 +32,18 @@ function y=dbplot()
 %     end
 
 %% author2
-    for m=1:leng
-        x=ofdm_signal();
-        [y1,y2,y3,p1s(m),p2s(m),p3s(m)]=cubic(x,1,1);
-    end
+%     for m=1:leng
+%         x=ofdm_signal();
+%         [y1,y2,y3,p1s(m),p2s(m),p3s(m)]=cubic(x,1,1);
+%     end
+% 
 
+%% 把下面的参数的p(i)改成要画的
+%%比如把OFDM注释以后，打开author2，把p(i)改成p1s(1)
+%%这样就等于画cubic算法里的第一支路的stem图 
     for i=1:leng
         for n=4:0.2:12
-            if (p1s(i)>=n && p1s(i)<(n+0.2))
+            if (p(i)>=n && p(i)<(n+0.2))
                 numX(int64((n-4)*5)+1)=numX(int64((n-4)*5)+1)+1;
             end
         end

matlab数据/OFDM.txt

+0.308586791992188	0.293241271972656	0.276849243164063	0.257483886718750	0.235721008300781	0.211956237792969	0.186378967285156	0.159213928222656	0.131997070312500	0.105480773925781	0.0807603759765625	0.0585694580078125	0.0395874023437500	0.0249008178710938	0.0142062988281250	0.00721051025390625	0.00321374511718750	0.00121063232421875	0.000380310058593750	9.26513671875000e-05	1.96533203125000e-05	2.99072265625000e-06	1.83105468750000e-07	6.10351562500000e-08	0	0	0	0	0	0	0

matlab数据/average.txt

+0.309573876953125	0.294565435791016	0.277727233886719	0.258801550292969	0.237467523193359	0.213865185546875	0.188500805664063	0.162103082275391	0.135370758056641	0.109384533691406	0.0850162048339844	0.0631082580566406	0.0445292358398438	0.0294977355957031	0.0182568786621094	0.0104669250488281	0.00553627319335938	0.00268894042968750	0.00118972167968750	0.000492956542968750	0.000188171386718750	6.69738769531250e-05	2.40539550781250e-05	8.64257812500000e-06	3.22265625000000e-06	1.16577148437500e-06	4.51660156250000e-07	2.38037109375000e-07	1.40380859375000e-07	5.49316406250000e-08	5.49316406250000e-08

matlab数据/cubic.txt

+0.312888433837891	0.297975384521484	0.281270385742188	0.262541284179688	0.241495922851563	0.218394757080078	0.193888757324219	0.168504113769531	0.143030627441406	0.118398034667969	0.0952629272460938	0.0744040344238281	0.0562838378906250	0.0412332641601563	0.0292687927246094	0.0201309753417969	0.0135679016113281	0.00894420776367188	0.00583164062500000	0.00380784301757813	0.00248375244140625	0.00166110229492188	0.00113763427734375	0.000795220947265625	0.000576391601562500	0.000434857177734375	0.000344183349609375	0.000275695800781250	0.000229809570312500	0.000196057128906250	0.000174279785156250

matlab数据/第一篇论文图等资料/HDS数据.txt

+0.921940000000000	0.796920000000000	0.604220000000000	0.411280000000000	0.261560000000000	0.158460000000000	0.0920400000000000	0.0497800000000000	0.0255200000000000	0.0124200000000000	0.00664000000000000	0.00344000000000000	0.00154000000000000	0.000880000000000000	0.000460000000000000	0.000280000000000000	9.90000000000000e-05	3.10000000000000e-05	2.20000000000000e-05	

stemplot.m

-% function  stemplot()
 a=peak();
 b=sum(a);
 figure
 bar(b,'grouped');
-axis([20 61 0 8000])
-set(gca,'XTickLabel',4:12);
-set(gca,'YTickLabel',0:2000:8000);
-% end
+%下面三句针对不同情况来改变坐标范围
+% axis([20 61 0 8000])
+% set(gca,'XTickLabel',4:12);
+% set(gca,'YTickLabel',0:2000:8000);
+