Cognitive-Radio.zip_cognitive_cognitive radio

clear all; clc u=1000;%time bandwidth factor N=2*u;%samples a=2;%path loss exponent C=2;%constant losses Crs=10; %Number of cognitive radio users PdAnd=0; %----------Pfa------------% Pf=0.01:0.01:1; Pfa=Pf.^2; %---------signal-----% t=1:N; s1 = cos(pi*t); % s1power=var(s1); %-------- SNR ----------% % Snrdb=-15:1:15; Snrdb=15; Snreal=power(10,Snrdb/10);%Linear Snr % while Snrdb<15 for i=1:length(Pfa) lamda(i)=gammaincinv(1-Pfa(i),u)*2; %theshold % lamdadB=10*log10(lamda); %---------Local spectrum sensing---------% for j=1:Crs %for each node detect=0; % d(j)=7+1.1*rand(); %random distanse d=7:0.1:8; PL=C*(d(j)^-a); %path loss for sim=1:10%Monte Carlo Simulation for 100 noise realisation %-------------AWGN channel--------------------% noise = randn(1,N); %Noise production with zero mean and s^2 var noise_power = mean(noise.^2); %noise average power amp = sqrt(noise.^2*Snreal); s1=amp.*s1./abs(s1); % SNRdB_Sample=10*log10(s1.^2./(noise.^2)); Rec_signal=s1+noise;%received signal localSNR(j)=mean(abs(s1).^2)*PL/noise_power;%local snr Pdth(j,i)=marcumq(sqrt(2*localSNR(j)),sqrt(lamda(i )),u);%Pd for j node %Computation of Test statistic for energy detection Sum=abs(Rec_signal).^2*PL; Test(j,sim)=sum(Sum); if (Test(j,sim)>lamda(i)) detect=detect+1; end end %END Monte Carlo Pdsim(j)=detect/sim; %Pd of simulation for the j-th CRuser end PdAND(i)=prod(Pdsim); PdOR(i)=1-prod(1-Pdsim); end PdAND5=(Pdth(5,:)).^5; Pmd5=1-PdAND5; PdANDth=(Pdth(Crs,:)).^Crs; PmdANDth=1-PdANDth; %Probability of miss detection Pmdsim=1-PdAND; figure(1); plot(Pfa,Pmdsim,'r-*',Pfa,PmdANDth,'k-o',Pfa,Pmd5,'g-*') title('Complementary ROC of Cooperative sensing with AND rule under AWGN'); grid on axis([0.0001,1,0.0001,1]); xlabel('Probability of False alarm (Pfa)'); ylabel('Probability of Missed Detection (Pmd)'); legend('Simulation','Theory n=10','Theory n=5');