clzhang
(zhang)
1
ut=0.6;
ur=1-ut;
omiga=rand(1);
rita_t=5;
rita_r=5;
c_r=rita_r/omiga;
c_t=rita_t/omiga;
alpha=2.2;
d=50;
cvx_begin
variables Dr Dt D
maximize(Dr+Dt)
pt=Dt^alpha;
pr=Dr^alpha;
p=d^alpha;
P=sqrt(p0/p);
g=gP;
cr=norm(rr.diag(g),1)^2;
ct=norm(rt.diag(g),1)^2;
a=sigema/(p0ct);
b=sigema/(p0cr);
subject to
Dr>=urD;Dr>=1;
Dt>=utD;Dt>=1;
omiga(2^c_r-1)sigemapr/(p0creb1)-Pmaxeb1<=0;%%sigema=-80,eb1=0.8689
omiga(2^c_t-1)sigemapt/(p0cteb2)-Pmax*eb2<=0;%%eb2=0.1311
cvx_end
Some words in the following might help.
The words to follow from the preceding are:
As for infeasible problems, follow the advice, except for section 1, in https://yalmip.github.io/debugginginfeasible, which also applies to CVX.
The rest of that quote, relating to Successive Approximation method, is not applicable here.