基于博弈论的频谱分配的matlab程序

是认知无线电场景下，基于博弈论的频谱分配的matlab程序-Cognitiveradioscenario,basedongametheorymatlabspectrumallocationprocessclcclearallB=15;BER=10^(-4);K=1.5/(logm(0.2/BER));SNR=[8,10];k=log2(1+K.*SNR);r1=10;r2=12;x=0;y=1;z=1;%b=[0,0];%c=x+y*(sum(b));%p=r.*k.*b-b.*c;a(1)=0.001;fori=1:300a(2)=0.001;forj=1:300eigenvalue(1)=1-10/3*(2*a(1)*k(1)-a(1)*k(2)+2*a(2)*k(2)-a(2)*k(1))+10/3*((a(1)*(k(2)-2*k(1))*a(2)*(k(1)-2*k(2))+(2*a(2)*k(2)-a(2)*k(1)-2*a(1)*k(1)+a(1)*k(2))^2)^(0.5));eigenvalue(2)=1-10/3*(2*a(1)*k(1)-a(1)*k(2)+2*a(2)*k(2)-a(2)*k(1))-10/3*((a(1)*(k(2)-2*k(1))*a(2)*(k(1)-2*k(2))+(2*a(2)*k(2)-a(2)*k(1)-2*a(1)*k(1)+a(1)*k(2))^2)^(0.5));if(eigenvalue(1)1)&&(eigenvalue(1)-1)&&(eigenvalue(2)1)&&(eigenvalue(2)-1)a(2)=a(2)+0.002;endendifa(2)0a(2)=a(2)-0.002;elsea(2)=0;endf2(i)=a(2);f1(i)=a(1);a(1)=a(1)+0.002;endfigure(1)plot(f1,f2,'--r')axis([0,0.25,0,0.25])holdonB=15;BER=10^(-4);K=1.5/(logm(0.2/BER));SNR=[10,10];k=log2(1+K.*SNR);r1=10;r2=12;x=0;y=1;z=1;%b=[0,0];%c=x+y*(sum(b));%p=r.*k.*b-b.*c;a(1)=0.001;fori=1:300a(2)=0.001;forj=1:300eigenvalue(1)=1-10/3*(2*a(1)*k(1)-a(1)*k(2)+2*a(2)*k(2)-a(2)*k(1))+10/3*((a(1)*(k(2)-2*k(1))*a(2)*(k(1)-2*k(2))+(2*a(2)*k(2)-a(2)*k(1)-2*a(1)*k(1)+a(1)*k(2))^2)^(0.5));eigenvalue(2)=1-10/3*(2*a(1)*k(1)-a(1)*k(2)+2*a(2)*k(2)-a(2)*k(1))-10/3*((a(1)*(k(2)-2*k(1))*a(2)*(k(1)-2*k(2))+(2*a(2)*k(2)-a(2)*k(1)-2*a(1)*k(1)+a(1)*k(2))^2)^(0.5));if(eigenvalue(1)1)&&(eigenvalue(1)-1)&&(eigenvalue(2)1)&&(eigenvalue(2)-1)a(2)=a(2)+0.002;endendifa(2)0a(2)=a(2)-0.002;elsea(2)=0;endf2(i)=a(2);f1(i)=a(1);a(1)=a(1)+0.002;endfigure(1)plot(f1,f2,'-.*b')axis([0,0.25,0,0.25])B=15;BER=10^(-4);K=1.5/(logm(0.2/BER));SNR=[10,8];k=log2(1+K.*SNR);r1=10;r2=12;x=0;y=1;z=1;%b=[0,0];%c=x+y*(sum(b));%p=r.*k.*b-b.*c;a(1)=0.001;fori=1:300a(2)=0.001;forj=1:300eigenvalue(1)=1-10/3*(2*a(1)*k(1)-a(1)*k(2)+2*a(2)*k(2)-a(2)*k(1))+10/3*((a(1)*(k(2)-2*k(1))*a(2)*(k(1)-2*k(2))+(2*a(2)*k(2)-a(2)*k(1)-2*a(1)*k(1)+a(1)*k(2))^2)^(0.5));eigenvalue(2)=1-10/3*(2*a(1)*k(1)-a(1)*k(2)+2*a(2)*k(2)-a(2)*k(1))-10/3*((a(1)*(k(2)-2*k(1))*a(2)*(k(1)-2*k(2))+(2*a(2)*k(2)-a(2)*k(1)-2*a(1)*k(1)+a(1)*k(2))^2)^(0.5));if(eigenvalue(1)1)&&(eigenvalue(1)-1)&&(eigenvalue(2)1)&&(eigenvalue(2)-1)a(2)=a(2)+0.002;endendifa(2)0a(2)=a(2)-0.002;elsea(2)=0;endf2(i)=a(2);f1(i)=a(1);a(1)=a(1)+0.002;endfigure(1)plot(f1,f2,'-g')axis([0,0.25,0,0.25])B=15;BER=10^(-4);K=1.5/(logm(0.2/BER));SNR=[7,7];k=log2(1+K.*SNR);r1=10;r2=12;x=0;y=1;z=1;%b=[0,0];%c=x+y*(sum(b));%p=r.*k.*b-b.*c;a(1)=0.001;fori=1:300a(2)=0.001;forj=1:300eigenvalue(1)=1-10/3*(2*a(1)*k(1)-a(1)*k(2)+2*a(2)*k(2)-a(2)*k(1))+10/3*((a(1)*(k(2)-2*k(1))*a(2)*(k(1)-2*k(2))+(2*a(2)*k(2)-a(2)*k(1)-2*a(1)*k(1)+a(1)*k(2))^2)^(0.5));eigenvalue(2)=1-10/3*(2*a(1)*k(1)-a(1)*k(2)+2*a(2)*k(2)-a(2)*k(1))-10/3*((a(1)*(k(2)-2*k(1))*a(2)*(k(1)-2*k(2))+(2*a(2)*k(2)-a(2)*k(1)-2*a(1)*k(1)+a(1)*k(2))^2)^(0.5));if(eigenvalue(1)1)&&(eigenvalue(1)-1)&&(eigenvalue(2)1)&&(eigenvalue(2)-1)a(2)=a(2)+0.002;endendifa(2)0a(2)=a(2)-0.002;elsea(2)=0;endf2(i)=a(2);f1(i)=a(1);a(1)=a(1)+0.002;endfigure(1)plot(f1,f2,'-.y')axis([0,0.25,0,0.25])B=15;BER=10^(-4);K=1.5/(logm(0.2/BER));SNR=[8,8];k=log2(1+K.*SNR);r1=10;r2=12;x=0;y=1;z=1;%b=[0,0];%c=x+y*(sum(b));%p=r.*k.*b-b.*c;a(1)=0.001;fori=1:300a(2)=0.001;forj=1:300eigenvalue(1)=1-10/3*(2*a(1)*k(1)-a(1)*k(2)+2*a(2)*k(2)-a(2)*k(1))+10/3*((a(1)*(k(2)-2*k(1))*a(2)*(k(1)-2*k(2))+(2*a(2)*k(2)-a(2)*k(1)-2*a(1)*k(1)+a(1)*k(2))^2)^(0.5));eigenvalue(2)=1-10/3*(2*a(1)*k(1)-a(1)*k(2)+2*a(2)*k(2)-a(2)*k(1))-10/3*((a(1)*(k(2)-2*k(1))*a(2)*(k(1)-2*k(2))+(2*a(2)*k(2)-a(2)*k(1)-2*a(1)*k(1)+a(1)*k(2))^2)^(0.5));if(eigenvalue(1)1)&&(eigenvalue(1)-1)&&(eigenvalue(2)1)&&(eigenvalue(2)-1)a(2)=a(2)+0.002;endendifa(2)0a(2)=a(2)-0.002;elsea(2)=0;endf2(i)=a(2);f1(i)=a(1);a(1)=a(1)+0.002;endfigure(1)plot(f1,f2,'om')axis([0,0.25,0,0.25])legend('r1=8dB,r2=10dB','r1=10dB,r2=10dB','r1=10dB,r2=8dB','r1=7dB,r2=7dB','r1=8dB,r2=8dB')xlabel('a1')ylabel('a2')