目录
1.程序功能描述
2.测试软件版本以及运行结果展示
3.核心程序
4.本算法原理
5.完整程序
1.程序功能描述
基于自适应波束成形算法的matlab性能仿真,对比SG和RLS两种方法.
2.测试软件版本以及运行结果展示
MATLAB2022a版本运行
3.核心程序
..................................................................................
for ii = 1:MTKL
if SEL == 1
for i = 1:length(r)
r_(:,i) = SD'*r(:,i);
A_ = SD'*a;
%xx : x*
x_(i) = W_'*r_(:,i);
xx(i) = conj(x_(i));
%开始迭代
if i == 1
W_ = SD'*(inv(R)*a*inv((a'*inv(R)*a))*e);
SD = SD - mu1*xx(i)*(r(:,i)*W_' - inv(a' *a )*(a*W_')*(a'*r(:,i)));
else
SD = SD - mu1*xx(i)*(r(:,i)*W_' - inv(a' *a )*(a*W_')*(a'*r(:,i)));
W_ = W_ - mu2*xx(i)*(eye(D) - inv(A_'*A_)*A_*A_') *r_(:,i);
end
rx = corrmtx(a*Sig_train(:,i),M-1);
RS = rx'*rx;
rx = corrmtx(a*Sig_train(:,i),M-1);
ry = corrmtx(a*Sig_train(:,i)+Noise_train(:,i),M-1);
RI = rx'*ry;
end
SINR(D) = abs((W_'*SD'*RS*SD*W_)/(W_'*SD'*RI*SD*W_));
end
%**************************************************************************
%RLS***********************************************************************
if SEL == 2
alpha = 1;
P = zeros(M,M);
P_ = zeros(D,M);
for i = 1:length(r)
r_(:,i) = SD'*r(:,i);
Pdelay = P;
P = inv(R);
A_ = SD'*a;
P_delay = P_;
P_ = SD'*P;
SD = (P*a*A_')/(a'*P*a);
W_ = (P_*a)/(A_'*P_*a);
k = alpha*Pdelay*r(:,i)/(1+alpha*r(:,i)'*Pdelay*r(:,i));
P = alpha*Pdelay-alpha*k*r(:,i)'*Pdelay;
rx = corrmtx(a*Sig_train(:,i),31);
RI = rx'*rx;
rx = corrmtx(a*Sig_train(:,i),31);
ry = corrmtx(a*Sig_train(:,i)+Noise_train(:,i),31);
RS = rx'*ry;
end
SINR(D) = abs((W_'*SD'*RI*SD*W_)/(W_'*SD'*RS*SD*W_));
end
end
SINRs(:,ii) = SINR;
end
DD = D3(4:end);
SINRS2 = 20*log10(mean(SINRs(4:end,:),2));
figure;
plot(DD,SINRS2,'b-o');
grid on;
xlabel('Rank')
ylabel('SINR');
27_008m4.本算法原理
自适应波束成形是阵列信号处理中的关键技术，用于在空间上选择性地增强期望信号并抑制干扰信号。在多种自适应波束成形算法中，随机梯度（Stochastic Gradient，SG）算法和递归最小二乘（Recursive Least Squares，RLS）算法是两种常用的方法。
RLS的基本流程如下所示：
SG的基本流程如下所示：
5.完整程序
VVV
