瑞利信道
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2023年3月18日发(作者：8位二进制)实验1瑞利信道的仿真
1引言
中文名称：瑞利分布
英文名称：Rayleighdistribution
定义：控制分布宽度的形状参数值为2的韦布尔分布。该分布函数取决于一个调节参
数——尺度参数。
它表示一个均值为(0.5*π*σ^2)^(0.5)，方差为(2-0.5*π)*σ^2的平稳窄带高斯过程，其包络的
一维分布是瑞利分布。当一个随机二维向量的两个分量呈独立的、有着相同的方差的正态分
布时，这个向量的模呈瑞利分布。
2实验目的：用MATLAB软件仿真瑞利信道，
产生瑞利信道的随机数：
pdf=
Columns1through11
00.01740.03480.05220.06960.08690.1042
0.12150.13860.15570.1728
Columns12through22
0.18970.20650.22320.23980.25630.27270.2889
0.30490.32090.33660.3522
Columns23through33
0.36760.38280.39780.41260.42720.44160.4557
0.46970.48340.49680.5101
Columns34through44
0.52300.53570.54820.56040.57230.58390.5953
0.60640.61710.62760.6378
Columns45through55
0.64770.65740.66670.67560.68430.69270.7008
0.70850.71600.72310.7299
Columns56through66
0.73640.74260.74840.75400.75920.76410.7687
0.77290.77690.78050.7839
Columns67through77
0.78690.78960.79200.79410.79600.79750.7987
0.79960.80030.80060.8007
Columns78through88
0.80050.80000.79920.79820.79690.79540.7936
0.79160.78930.78680.7840
Columns89through99
0.78100.77780.77440.77070.76690.76280.7585
0.75410.74940.74460.7396
Columns100through110
0.73450.72910.72360.71800.71220.70620.7002
0.69400.68760.68120.6746
Columns111through121
0.66790.66110.65430.64730.64020.63310.6259
0.61860.61120.60380.5963
Columns122through132
0.58880.58120.57360.56600.55830.55060.5428
0.53510.52730.51960.5118
Columns133through143
0.50400.49620.48850.48070.47300.46530.4575
0.44990.44220.43460.4270
cdf=
Columns1through11
00.00010.00030.00080.00140.00220.0031
0.00430.00560.00700.0087
Columns12through22
0.01050.01250.01460.01690.01940.02210.0249
0.02780.03100.03430.0377
Columns23through33
0.04130.04500.04900.05300.05720.06150.0660
0.07070.07540.08030.0854
Columns34through44
0.09050.09580.10120.10680.11240.11820.1241
0.13010.13620.14250.1488
Columns45through55
0.15520.16180.16840.17510.18190.18880.1957
0.20280.20990.21710.2244
Columns56through66
0.23170.23910.24660.25410.26160.26920.2769
0.28460.29240.30020.3080
Columns67through77
0.31580.32370.33160.33960.34750.35550.3635
0.37140.37940.38750.3955
Columns78through88
0.40350.41150.41950.42740.43540.44340.4513
0.45930.46720.47500.4829
Columns89through99
0.49070.49850.50630.51400.52170.52930.5369
0.54450.55200.55950.5669
Columns100through110
0.57430.58160.58890.59610.60320.61030.6174
0.62430.63120.63810.6449
Columns111through121
0.65160.65820.66480.67130.67770.68410.6904
0.69660.70280.70880.7148
Columns122through132
0.72080.72660.73240.73810.74370.74930.7547
0.76010.76540.77070.7758
PDF：
00.511.522.53
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probabilitydistributionfunction
CDF：
00.511.522.53
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cumulativedistributionfunction
瑞利数据的均植和方差:
均值：jzpdf=0.3321
jzcdf=0.6829
方差：fcpdf=0.0843
fccdf=0.1246
3实验内容：编写程序代码，程序框图
x=[0:0.01:3];%取样
var=cov(x);%方差
pdf=raylpdf(x,var);%概率密度分布函数
subplot(2,1,1);
plot(x,pdf);
title('probabilitydistributionfunction');
jzpdf=mean(pdf);%pdf均值
fcpdf=cov(pdf);%pdf方差
cdf=raylcdf(x,var);%积累密度分布函数
subplot(2,1,2);
plot(x,cdf);
title('cumulativedistributionfunction');
jzecdf=mean(cdf);%cdf均值
fccdf=cov(cdf);%cdf方差
4实验结果与分析
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probabilitydistributionfunction
0123
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cumulativedistributionfunction
参考文献：
[1]MathWorks,MATLABR2006a,2006.
[2]MathWorks,MATLABR2007a,2007.
[3]MathWorks,MATLABR2008a,2008.
[4]百度百科，/view/