基于机器学习的高阶调制星座设计

 2022-05-12 20:56:42

论文总字数:21598字

毕业设计软硬件验收表

任务书规定完成的软硬件内容及规定的技术指标:(学生填写)

完成了星座的联合界及误码率仿真性能测试:

联合界:

clc

clear all

load('s');

figure(1);

axis([-1 1 -1 1]);

S= s(:,1) 1i.*s(:,2);

scatter(real(S),imag(S))

xlabel('实数'); ylabel('虚数');title('16-QAM(12dB训练)')%随机产生星座坐标并得到星座图;

p_avg=sum(sum(s.*s))/16 %点乘即两个矩阵的对应位置相乘

x_avg=sum(s(:,1))/16

y_avg=sum(s(:,2))/16

M =16;

distance = 100.*ones(M,M);

for i= 1: 1: M

for j =1 : 1 : M

if i~=j

distance(i,j)=sum((s(i,:)-s(j,:)).^2,2);%b=sum(a,dim); a表示矩阵;dim等于1或者2,1表示每一列进行求和,2表示每一行进行求和;表示每列求和还是每行求和;b表示求得的行向量。

else

distance(i,j)=distance(i,j);

end

end

end

min_1 = min(min(distance))%如果A是一个矩阵,min(A)将A的每一列作为一个向量,返回一行向量包含了每一列的最小元素。

array = sort(distance,1);

%sort(A)若A是向量不管是列还是行向量,默认都是对A进行升序排列。sort(A)是默认的升序,而sort(A,'descend')是降序排序。

%sort(A)若A是矩阵,默认对A的各列进行升序排列

%sort(A,dim)

%dim=1时等效sort(A)

%dim=2时表示对A中的各行元素升序排列

I =ones(1,M);

specture =reshape(distance-100.*diag(I),1,M*M);

test = hist(specture,30)

figure(2)

stem(test)

h= findobj(gca,'Type','patch');

set(h,'Facecolor',[1 1 1])

% set(gcf,'Color',[1 1 1])

%erfc估计部分(成对差错概率):

p = 1 /M;

Pe = zeros(1,M); %用于说明生成的误差函数的上界

pe= 0;

ser_t=[];

for SNR =1:1:20

EsN0= 10^(SNR/10);

for m= 1: M

Sum = 0;

for n=1:M

if m ~= n

Sum = Sum erfc(sqrt(distance(m,n))*sqrt(EsN0)*0.5)*p;

end

end

Pe(1,m) = Sum ;

end

pe = 0.5* sum(Pe)

ser_t=[ser_t,pe];

end

% Pe(1,m)=Pe(1,m).*p;

figure(3)

semilogy(1:1:20,ser_t)

xlabel('信噪比(SNR)');

ylabel('成对差错概率');

legend('ser_t')

save('ser_t','ser_t')

% Pe_max = erfc(sqrt(0.31)*sqrt(EsN0)*0.5)

%%根据联合界来求性能

%Pe_U=zeros(1,16);

%for SNR=1:1:16

% N0=1/(10^(SNR/10));

% Pe_U(SNR)=(16-1)/2*erfc(min_1/(2*sqrt(N0)));

%end

%figure(4)

%SNR=1:1:16;

%log_Pe_U=log10(Pe_U);

%plot(SNR,log_Pe_U);

%semilogy(1:1:16,Pe_U(SNR));

%for x=1:1:M

% semilogy(x,Pe_U(x));

%end

%xlabel('信噪比(SNR)');

%ylabel('误符号率');

%semilogy(x,Pe_U(x));

%fugure(5)

误码率仿真:

symbol=50000;

nb = symbol*4;

data= randi([0,1],1,nb); %生成1*200000矩阵且每个元素取值随机为0或1

modu = modu_random_s(data,nb);

error=0;

BER = 0;

snr = 1:1:8;

len= length(snr);

ber = [];

ser=[];

%过信道

for snr =1:1:20

receive = awgn(modu,snr,'measured');

demodu = demodu_random_matrix(receive,nb);

% demodu=1:1:8;

% modu_2 = modu_random_s(demodu,nb);

% error = sum(mod(demodu-data,2));

% ber=[ber,error/nb];

for len=1:1:symbol

if(demodu(len)~=modu(len))

error = error 1;%统计差错

end

end

ser=[ser,error/symbol];

error = 0;

end

save('ser2','ser')

SNR = 1:1:20;

semilogy(SNR,ser,'ro-') %y轴是对数坐标系

% hold on ;

% %qpsk 误比特率理论图

% r=1:0.1:8;

% x=10.^(r/10);

% pc=(1-0.5*erfc(sqrt(x/2))).^2;

% pe=1-pc;

% per=0.5*erfc(sqrt(x/2));

% % pe=erfc(sqrt(x/2));

% semilogy(r,per,'b--');grid on;

% % plot(r,pe);grid on;

xlabel('信噪比(dB)'); ylabel('误码率');

title('16-QAM过白噪声信道仿真图')

legend('仿真值') ;grid on; %%备注:12.7dB时达到噪声容限

调制函数:

function modu_data=modu_random_s(code_word,number)

load s;

random_s=s;

for i=1:number/4

hexbit = code_word(4*i-3)*8 code_word(4*i-2)*4 code_word(4*i-1)*2 code_word(4*i)*1;%将每一位由二进制转化为十进制再用case进行判断,将数组每四位编成一组转换成十进制数,并根据十进制数进入case得到对应复数;

modu(i)=random_s(hexbit 1,1) 1i*random_s(hexbit 1,2);

% switch hexbit

% case 0, modu(i) = random_s(1,1) 1i*random_s(1,2);

% case 1, modu(i) = random_s(2,1) 1i*random_s(2,2);

% case 2, modu(i) = random_s(3,1) 1i*random_s(3,2);

% case 3, modu(i) = random_s(4,1) 1i*random_s(4,2);

% case 4, modu(i) = random_s(5,1) 1i*random_s(5,2);

% case 5, modu(i) = random_s(6,1) 1i*random_s(6,2);

% case 6, modu(i) = random_s(7,1) 1i*random_s(7,2);

% case 7, modu(i) = random_s(8,1) 1i*random_s(8,2);

% case 8, modu(i) = random_s(9,1) 1i*random_s(9,2);

% case 9, modu(i) = random_s(10,1) 1i*random_s(10,2);

% case 10, modu(i) = random_s(11,1) 1i*random_s(11,2);

% case 11, modu(i) = random_s(12,1) 1i*random_s(12,2);

% case 12, modu(i) = random_s(13,1) 1i*random_s(13,2);

% case 13, modu(i) = random_s(14,1) 1i*random_s(14,2);

% case 14, modu(i)= random_s(15,1) 1i*random_s(15,2);

% case 15, modu(i) = random_s(16,1) 1i*random_s(16,2);

% end

end

load('mean_dist')

%modu_data=modu./sqrt(mean_dist);%能量归一化

modu_data=modu;

解调函数:

function demodu=demodu_random_matrix(ant_laymap_out,number) QAM解调

%symbol=50000;

load s;

random_s=s;

%number=;

for i=1:1:number/4

for j=1:1:16

tmp_real=real(ant_laymap_out(i));

tmp_imag=imag(ant_laymap_out(i));

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