www.pudn.com > ica_cdma.rar > ica_cdma.m
clear all
clc
%----------------初始量的声明------------------------------
K=4; %输入信号的个数
len_seq=50; %各个信号序列的长度
m=5; %PN序列的阶数
len_chip=2^m-1; %PN序列的长度
sgma=1; %噪声平均功率
snr=20; %输入信噪比
Eb=2*sgma^2*10^(snr/10); %发送信号的功率
E_chip=Eb/len_chip; %单位片长的功率
initial_code=1; %差分编码的初始值
R=30; % Analog Signal Simulation rate
%----------------随机生成K个源信号---------------------------
orig_seq=sign(rand(K,len_seq)*2-0.5);
%--------------对orig_seq进行差分编码-----------------------
x=(orig_seq>0); %双极性码转化为单极性码
y=zeros(K,len_seq);
%x
for k=1:K %循环为差分编码
temp_code=initial_code;
for i=1:length(x(1,:))
y(k,i)=xor(x(k,i),temp_code);
temp_code=y(k,i);
end
end
d_code_seq=(y==1)-(y==0) ; %单极性转换为双极性，d_code_seq为差分编码后的序列
%---------------扩频编码----------------------------------------------------
%-----------产生K个GOLD码序列-----------------
gold_seq=gold_generate(m);
pn=(gold_seq==1)-(gold_seq==0);
%----------对各个序列进行扩频------------------
for i=1:K
spreaded_seq(i,:)=ds_sp(d_code_seq(i,:),pn(i,:),len_seq,len_chip);
end
%---------进行波形整形，通过的是Rectangular Filter-----------------------------------------
for i=1:K
chips_out=spreaded_seq(i,:)';
chips = [chips_out, zeros(len_chip*len_seq, R-1)]; % Pulse generation
chips = reshape(chips.' , len_chip*len_seq*R, 1);
L = R;
L_2 = floor(L/2);
MF = ones(L, 1);
MF = MF/sqrt(sum(MF.^2)); %MF为 mathed filter taps
TxOut = sqrt(R)*conv(MF, chips)/sqrt(2);
TxOut = TxOut(L_2+1: end - L_2);
tx(i,:)=TxOut';
end
spreaded_seq=tx; %这里的spreaded_seq为整形后的信号矩阵
%*******************信号的混合加噪声**********************************
A=rand(K); %A为混合矩阵
X=A*sqrt(E_chip)*spreaded_seq+sgma*randn(K,length(spreaded_seq)); %X为混迭信号矩阵
%**********************************************
for i=1:K
X(i,:)=X(i,:)-1/(len_chip*len_seq*R)*sum(X(i,:));
end
%----------对混迭信号进行预白化---------------------------------------------
[y x]=eig(cov(X',1));
%---特征值按大小排，相应的特征矢量也进行排序----
for i=1:K
for j=(i+1):K
temp=x(i,i);
temp_2=y(:,i);
if temp1-epsilon) %判断是否收敛
exit=1;
end
iter=iter+1;
end
end
out=W'*Y; %out为输出矩阵
%**************进行匹配滤波后抽样******************
for i=1:K
RxIn=out(i,:)';
L = length(MF); %MF为 mathed filter taps
L_2 = floor(L/2);
rr = conv(flipud(conj(MF)), RxIn);
rr = rr(L_2+1: end - L_2);
Rx = sign(real(rr(1:R:end))) ;
rx(i,:)=Rx';
end
huang=sign(rx); %huang为匹配滤波抽样后的矩阵
%*******************通过判断与PN的相关性确定各个信号的顺序********************
y=zeros(1,4);
for i=1:K
[x_1(i,1:K) y(i)]=xiang_guan(huang(i,:),pn,len_seq,len_chip,K);
end
x_1 %得到的相关性矩阵 x_1=[huang(1,:)*pn1 huang(1,:)*pn2 huang(1,:)*pn3 huang(1,:)*pn4
% huang(2,:)*pn1 huang(2,:)*pn2 huang(2,:)*pn3 huang(2,:)*pn4
% huang(3,:)*pn1 huang(3,:)*pn2 huang(3,:)*pn3 huang(3,:)*pn4
% huang(4,:)*pn1 huang(4,:)*pn2 huang(4,:)*pn3 huang(4,:)*pn4]
%上面的huang(i,:)*pnj,代表他们之间的相关值
zhuan=zeros(K); %zhuan为信号顺序转换矩阵
for i=1:K
zhuan(y(i),i)=1;
end
seq_separated=zhuan*huang; %seq_separated为已经变为与原来信号矩阵顺序相同
%**************************************************************************
%--------分离得到的信号进行解扩---------------------------------------------
rec_seq_temp=despread_spectrum(seq_separated,pn,len_seq,len_chip);
%--------为测误码率而进行修正相反的幅度----------------------------------------
rec_seq=correct(d_code_seq,rec_seq_temp);
%%-----------差分译码过程------------------------------------------------------
y=rec_seq>0;
for k=1:K
temp_dcode=initial_code;
for i=1:length(y(1,:))
z(k,i)=xor(temp_dcode,y(k,i));
temp_dcode=y(k,i);
end
end
p=2*z-1;
rec_seq=p;
%-----------统计误差-------------------------------------------------------
num_error=sum((rec_seq~=orig_seq)');
p_error=sum(num_error)/(len_seq*K) %误码率