The problem to be solved comes from a paper.So make sure this question is feasible. I want to reproduce the paper model, but there are problems that cannot be solved during optimization.

Original question：

my model

cvx_begin SDP

variable W semidefinite

variable Sigma semidefinite

A2=W+(1-beta

*2.^Rs)*

real(trace (Hl(A2-Z)))-real(2

*Sigma;*

R2=Lemma2(Z,A2,cl);

A1=W-(beta-1)R1)<= real(beta-1);R2=Lemma2(Z,A2,cl);

A1=W-(beta-1)

*Sigma;*

R1=Lemma1(Z,A1,dl);

minimize trace(W+Sigma)

subject to

real(trace (Gl(A1+Z)))+real(2R1=Lemma1(Z,A1,dl);

minimize trace(W+Sigma)

subject to

real(trace (Gl

real(trace (Hl

*R2) >= real(beta*(2^Rs)-1);

real(trace (W+Sigma)) <= Pmax;

cvx_end

Lemma2 and Lemma1 are the defined function.I have been troubled for a long time, I hope I can get your help, thank you！