I am trying to minimize the position error bound (PEB) with power constraints. The code is below:

```
omega_g = exp(1i*2*pi.*rand(N_ris,M));
cvx_solver sedumi
cvx_begin sdp
variable X(N_t, N_t) hermitian
expressions J_gamma(2,2) PEB(2,2)
for m=1:M
k1=2/(sigma^2);
qwmn=abs((betaR+1j*betaI)*x_m(m)*alpha)^2;
k3=abs(x_m(m)*alpha)^2;
k4=(betaR-1j*betaI)*k3;
J_gamma(1,1) = J_gamma(1,1) + k1*qwmn*(a_K_a)'*a_K_a*cdot_ris'*omega_g(:,m)*
(omega_g(:,m))'*cdot_ris*a_B_d'*X*a_B_d; %(:,:,m)
J_gamma(2,2) = J_gamma(2,2) + k1*qwmn*(adot_K_a')*adot_K_a*c_ris'*omega_g(:,m)*
(omega_g(:,m))'*c_ris*(a_B_d')*X*a_B_d;
J_gamma(1,2) = J_gamma(1,2) + k1*qwmn*(a_K_a)'*adot_K_a*c_ris'*omega_g(:,m)*
(omega_g(:,m))'*cdot_ris*a_B_d'*X*a_B_d;
J_gamma(2,1) = (J_gamma(1,2))';
end
PEB = T*J_gamma*transpose(T);
% Objective: Minimize the Position Error Bound (PEB)
% PEB is based on the determinant of the FIM
minimize(trace_inv(PEB)) % Minimize the PEB
subject to
X == hermitian_semidefinite(N_t);
real(trace(X)) <= 1;
```

cvx_end

I am getting a warning message as follows: "This linear matrix inequality appears to be unsymmetric. This is

very likely an error that will produce unexpected results. Please check

the LMI; and, if necessary, re-enter the model. "

Can someone please help me where I am getting the model wrong? I checked the PEB matrix and is symmetric.