Cannot perform the operation: {positive constant} ./ {convex}

Nonconvex
1

it told me that this row z2= z2+A(k,i)(p0^2)./(H^2+C2(i)) exists mistake as shown in the title
cvx_begin
expression C2(2K,1);
variable q(2,1);
expression R_UAV_K(1,2K);
expression R_K_UAV(1,2K);
expression R_min(2K,1);
for k=1:1:2K

    P(k)=1;
    U(: , k)=[x_user(k);y_user(k)];                  
    XL(k)=norm(U(:,k)-qL(:,1))^2;                    
    d(k)=(H^2+XL(k));                               
    h(k)= p0./sqrt(d(k));                            
    C2(k)=pow_pos(norm(U(:,k)-q(: ,1)),2);          
end
fai=sigma./(P_UAV*(p0^2));
delta=zeros(2*K,1);         
z1=0;
for k=1:1:2*K
    for i=1:1:2*K
        z1=z1+b_down(i)*B(k,i);
    end
    delta(k)=fai*(H^2)+z1;
    R_UAV_K(k)= log2(1+b_down(k)./(delta(k)+fai*XL(k)))-b_down(k)*fai*(C2(k)-XL(k))./((log(2))*(delta(k)+b_down(k)+fai*XL(k))*(delta(k)+fai*XL(k)));
end                                 

z2=0;
tao=zeros(1,2*K);     
for k=1:1:2*K
    for i=1:1:2*K  
        if A(k,i)~=0
        z2= z2+A(k,i)*(p0^2)./(H^2+C2(i));
           end
    end
    tao(k)=z2;
    R_K_UAV(k)=log2(1+P(k)*p0^2./((tao(k)+sigma)*(H^2+XL(k))))-p0^2*P(k)*(C2(k)-XL(k))./(log(2)*(H^2+XL(k))*(H^2+XL(k)+p0^2*P(k)));
end

for k=1:1:2*K
    R_min(k)=min( R_K_UAV(2*K-k+1),R_UAV_K(k));
end


maximize  (sum(R_min))
subject to
for k=1:1:2*K
    for i=1:1:2*K
        if A(k,i)==1
            %C2(k)<=C2(i);
            pow_pos(norm(U(:,k)),2)-pow_pos(norm(U(:,i)),2)+2*q(1,1)*(U(1,i)-U(1,k))+2*q(2,1)*(U(2,i)-U(2,k))<=0;
        end
    end
end

cvx_end

qL=q;
scatter(qL(1,1),qL(2,1),260,'m','p','filled');

end

2

z2 goes into tao which goes into R_K_UAV, which needs to be concave. So you need to first prove that R_K_UAV is concave.

Why does your code set R_K_UAV(k) in 2 different double for loops?

3

I am sorry to say that R_K_UAV is convex

4

R_K_UAV is used as the argument of min, so it needs to be concave, which would make the argument of maximize in the objective concave, which is needed to make the optimization problem convex.

5

Thank you for your reply! I got you what you said!