micro_test1.m

此程序为MATLAB程序

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Part74设备（无线麦克风）检测 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5%%%%%%%%%%%%%%%%%%%%%%%%%%%%
clear all;
close all;
echo on;
connections1=[1 0 1 0 0 ];           
connections2=[1 1 1 0 1 ];         
gold_seq=PN_1(connections1,connections2);                                                                      
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% AWGN noise %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%555%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
val=0.5;
%for snr=0:val:20
for snr=0:val:20
   col=(snr+val)/val;                           % 数组长度
           Ta(col)=0;                           % 加权阈值   
           Tb(col)=0;                           % 自适应双阈值
           Tc(col)=0;                           % 自适应单阈值
           Td(col)=0;                           % 固定阈值
          % 检测概率   
           Fa(col)=0;                           % 加权阈值   
           Fb(col)=0;                           % 自适应双阈值
           Fc(col)=0;                           % 自适应单阈值
           Fd(col)=0;                           % 固定阈值
          % 漏检概率
           Ea(col)=0;                           % 加权阈值   
           Eb(col)=0;                           % 自适应双阈值
           Ec(col)=0;                           % 自适应单阈值
           Ed(col)=0;                           % 固定阈值
  
for m=1:1:10                                                     % 仿真次数
to=0.2;                                                             % 接收信号的持续时间     
[R,r] = wireless_microphone(to);                                    % 待感知信号
signal_power = 6225.6;                                              % 信号功率
SIGMA=sqrt(6225.6/10^(0.1*snr));
noise = zeros(1,2048);
MU = zeros(1,2048);    
noise = normrnd(MU,SIGMA);                                          % 产生AWGN

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%  transmitted signal   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% 假设主用户随机占用信道

for j=1:1:8                                                        % 改变伪随机序列长度，随机改变主用户的占用情况
    for k=1:1:8                                
        if (gold_seq(j,k)==1)                                     
            xx(1,(length(r)*(k-1)+1):length(r)*k)=r+noise;         % 伪随机码为1，主用户占用信道；
        else   
            xx(1,(length(r)*(k-1)+1):length(r)*k)=noise;           % 伪随机码为0，主用户未占用信道；只有存在噪声
        end
    end
end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Muti-cycles detection %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
nn=noise(1,1:2048);
rr=r(1,1:2048);
S=40;                                                             % 循环周期数S，可改为 20,40,50
[l_noise,threshold]=estimate(nn,S);
l_noise=abs(l_noise);                                             % 噪声估计值
[l_signal,threshold]=estimate(rr,S);
l_signal=abs(l_signal);                                           % 信号估计值
    for ii=1:8
        rr(1,1:2048)= xx(1,(2048*(ii-1)+1):2048*ii);              % 每 0.2s 就感知一次信道，进行多周期循环检测
       [ll_signal,threshold]=estimate(rr,S);
       ll(ii,m)=abs(ll_signal);  
    end  
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%     计算自适应阈值    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%      `
     
       Pfa=0.3;                                                      % 虚警概率可改：0.05,0.1,0.2,0.3
       aa=sqrt(2*log10(1./Pfa)); 
       th=l_noise*aa;
       adap_thres(m)=th;
       %m=m+1;
   end  
                th2=mean(l_noise(1,:));        
                th3=mean(ll_signal(1,:)); 
                snr_avg=(th3.^2)/(th2.^2);
                
                FT=0.3;                                               % 指数加权因子FT可改为 0.1,0.3,0.9,1.2
                th4=threshold*(sqrt(snr_avg)/th3).^FT;
              
                K=0.2;                                                % 乘性因子K可改为 0.01,0.03,0.1,0.2
                th6(1,:)=K*l_noise(1,:)/aa;
                ouyany=5
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%  判决   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%              

                [FA,EA,TA]=decisionv(ll,th4,gold_seq);                % 加权阈值的判决 
                [FB,EB,TB]=decisionv(ll,th6,gold_seq);            % 自适应双阈值的判决 
                [FC,EC,TC]=decisionv(ll,adap_thres,gold_seq);     % 自适应单阈值的判决 
                [FD,ED,TD]=decisionv(ll,threshold,gold_seq);      % 固定阈值的判决  
                  ouyany=4
          %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 统计判决结果   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%                              
          % 虚警概率
          Ta(col)=TA/20*8;   % 加权阈值   
          Tb(col)=TB/20*8;   % 自适应双阈值
          Tc(col)=TC/20*8;   % 自适应单阈值
          Td(col)=TD/20*8;   % 固定阈值
          
          % 检测概率   
          Fa(col)=FA/20*8;   % 加权阈值   
          Fb(col)=FB/20*8;   % 自适应双阈值 
          Fc(col)=FC/20*8;   % 自适应单阈值 
          Fd(col)=FD/20*8;   % 固定阈值
          
          % 漏检概率
          Ea(col)=EA/20*8;  % 加权阈值
          Eb(col)=EB/20*8;  % 自适应双阈值
          Ec(col)=EC/20*8;  % 自适应单阈值    
          Ed(col)=ED/20*8;  % 固定阈值
          
end
[Fa1]=averge(Fa);
[Fb1]=averge(Fb);
[Fc1]=averge(Fc);
[Fd1]=averge(Fd);

[Ea1]=averge(Ea);
[Eb1]=averge(Eb);
[Ec1]=averge(Ec);
[Ed1]=averge(Ed);

[Ta1]=averge(Ta);
[Tb1]=averge(Tb);
[Tc1]=averge(Tc);
[Td1]=averge(Td);

Fa1=sort(Fa1);
Fb1=sort(Fb1);
Fc1=sort(Fc1);
Fd1=sort(Fd1);

Ta1=sort(Ta1);
Tb1=sort(Tb1);
Tc1=sort(Tc1);
Td1=sort(Td1);

Ea1=sort(Ea1);
Eb1=sort(Eb1);
Ec1=sort(Ec1);
Ed1=sort(Ed1);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Ed_maximum=max(Ed(:));
for n=1:2:41
    tao=log(1-Td(n))/log(Ed(n));
         Ni(n)=log((1-Fd(n))/Fd(n))*(tao/((((Ed_maximum*((1-Fd(n))^(-1))-1)^(-1))*(tao))-tao));   % 每种SNR下需要实际频谱感知的次数
         Nj(n)=round(abs(Ni(n)));
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%  plot detection picture %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
figure(1)
snr=0:1:20; 
k=1:2:41;
plot(snr,Fa1(k),'-ro',snr,Fb1(k),'--k*',snr,Fc1(k),'-cd',snr,Fd1(k),'b+-')
legend('(1)自适应加权阈值','(2)自适应双门限阈值','(3)自适应单门限阈值','(4)固定阈值')

grid on ;  
xlabel('SNR/db')                
ylabel('Pd')  
title('无线麦克风信号正确检测概率图');

figure(2)
subplot(2,1,1)
plot(xx);
xlabel('时间[s]');
ylabel('幅度[V]');
title('间隙发送无线麦克风信号');
subplot(2,1,2)
bar(ll);
xlabel('时间[s]');
ylabel('检测估计值');
title('检测估计值图');

figure(3)
snr=0:1:20; 
k=1:2:41;
plot(snr,Ta1(k),'-ro',snr,Tb1(k),'--k*',snr,Tc1(k),'-cd',snr,Td1(k),'b+-')   
legend('(1)自适应加权阈值','(2)自适应双门限阈值','(3)自适应单门限阈值','(4)固定阈值')


grid on ;  
xlabel('SNR/db')                
ylabel('Pf')  
title('无线麦克风信号虚警概率图');

figure(4)
snr=0:1:20; 
k=1:2:41;
plot(snr,Ea1(k),'-ro',snr,Eb1(k),'--k*',snr,Ec1(k),'-cd',snr,Ed1(k),'b+-')   
legend('(1)自适应加权阈值','(2)自适应双门限阈值','(3)自适应单门限阈值','(4)固定阈值')

grid on ;  
xlabel('SNR/db')                
ylabel('Pm')  
title('无线麦克风信号漏检概率图');