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⛄ 内容介绍
频谱感知的目标是在尽量避免对 主用户造成干扰的条件下为感知用户提供尽可能多的频谱接入机会.由于单用户频谱检测算法的局限性,协作频谱感知被提了出来.在满足对主用户干扰限度的条件 下,为了使单个授权信道的频谱感知效率达到最大,引入一种新的协作频谱感知机制,联合优化包括感知时间,传输时间,参与协作的感知用户数目在内的感知参 数,并通过穷尽搜索算法得到最优解.在此基础上研究了多个授权信道情况下的频谱感知效率问题,提出了一种授权信道选择分配方案.仿真结果验证了所提方法的 有效性.
⛄ 完整代码
clc;
close all;
clear all;
%This program is for optimization of spectrum sensing in
%Cognitive radio network.
N=20;
j=1;
tt=[];
err2=[];
Pmi=[];
Pdc=[];
error=[];
err1=[];
K=10;
snr=10;
Qd=0;
Qf=0;
tt=10:0.5:60;
vec=['-+','-o','-v','-d','->','-x','-s','-<','-*','-^'];
for n=1:1:10
s=ones(1,N);
w=randn(1,N);
u=N/2; %Time-delay bandwidth product
for t=10:0.5:60
Qd=0;
Qf=0;
SNR=10^(snr/10); %for linear scale
a=sqrt(2*SNR);
b=sqrt(t);
Pd = marcumq(a,b,u ); % AVG. PROB OF DETECTION(computes the generalized Marcum Q)
Pf = gammainc((t/2),u,'upper');% AVG. PROB OF FALSE ALARM(compute incompelete gamma function)
Pm=1-Pd; %AVG. PROB OF MISSED DETECTION OVER AWGN
for l=n:1:K
Qd=Qd+(factorial(K)*(Pd^l)*((1-Pd)^(K-l))/(factorial(l)*factorial(K-l)));
Qf=Qf+(factorial(K)*(Pf^l)*((1-Pf)^(K-l))/(factorial(l)*factorial(K-l)));
end
Qm=1-Qd;
err=Qf+Qm;
err1=[err1 err];
end
end
l=1;
i=1;
for j=1:1:10
semilogy(tt,err1(i:i+100),vec(l:l+1),'LineWidth',1.5)
i=i+101;
l=l+2;
hold on;
end
grid on;
ylabel('Total Error rate');
xlabel('Threshold');
%----------------------Energy Detection----------------------------------------
n=5;
rel=10000;
tt1=10:0.5:60;
er1=[];
for t=10:0.5:60
Pdc=0;
Pfc=0;
Qd=0;
Qf=0;
Qm=0;
for i=1:1:rel
SNR=10;
snr=10^(SNR/10);
s=ones(1,N);
w=randn(1,N);
vari=var(w); %variance of noise
Es=sum(s.^2);
N02=(Es)/(2*snr);
x1=s+w;
x2=w;
W=1; %Time-delay bandwidth product
E0=(sum(x2.^2))/((W*N02));
E1=(sum(x1.^2))/((W*N02));
if E1>t
Pdc=Pdc+1;
else
end
if E0>t
Pfc=Pfc+1;
else
end
end
Pd=Pdc/rel;
Pf=Pfc/rel;
for l=n:1:K
Qd=Qd+(factorial(K)*(Pd^l)*((1-Pd)^(K-l))/(factorial(l)*factorial(K-l)));
Qf=Qf+(factorial(K)*(Pf^l)*((1-Pf)^(K-l))/(factorial(l)*factorial(K-l)));
end
Qm=1-Qd;
er=Qf+Qm;
er1=[er1 er];
end
hold on;
semilogy(tt1,er1,'*r')
grid on;
ylabel('Total Error rate');
xlabel('Threshold');
legend('n=1','n=2','n=3','n=4','n=5','n=6','n=7','n=8','n=9','n=10','n=5 by modelling');
⛄ 运行结果
⛄ 参考文献
[1]胡晓宁,胡捍英,仵*. 认知无线电协作频谱感知机制的优化[J]. 数据采集与处理, 2011, 26(6):6.