How to solve these Generalized eigenvalue programming using CVX?

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indent preformatted text by 4 spaces
clc,
clear;
close all;
epsilon = 1e-3;
low_bod = -200;
upper_bod = 200;
iter_num = 100;
Nt = 10;
Ne = 4;
sigma = 1;
H = rand(Nt,Ne);
Pmax = 1;
t = 100;
lambda0 = 100;
val = zeros(iter_num,1);
for iter = 1:100
    
 cvx_begin quiet
    variable F1(Nt,Nt) hermitian  semidefinite
    variable F2(Nt,Nt) hermitian  semidefinite
    subject to
        lambda0*(H'*F2*H+sigma^2*eye(Ne))- (H'*F1*H)==semidefinite(Ne)
        (H'*F2*H+sigma^2*eye(Ne)) ==semidefinite(Ne)
        real(trace(F1) + trace(F2))<=Pmax
cvx_end


cvx_begin sdp quiet
    variable lambda
    minimize (lambda)
    subject to
    lambda*(H'*F2*H+sigma^2*eye(Ne))- (H'*F1*H)==semidefinite(Ne)

    
cvx_end
lambda0 = lambda;
val(iter) = lambda;

disp(iter)
end

e=eig((H'*F2*H+sigma^2*eye(Ne))\(H'*F1*H));
min(e)

i