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=g*P;*

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>=ut*D;Dt>=1;*

omiga(2^c_r-1)*sigema*pr/(p0*cr*eb1)-Pmax*eb1<=0;%%sigema=-80,eb1=0.8689*

omiga(2^c_t-1)*sigema*pt/(p0*ct*eb2)-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.