I want to find a diagonal matrix P which should maximize the sum of the eigenvalues of the Hermitian matrix H*H’, obtained as shown below. The matrices G, H_ia, and H_ba are all complex and their dimensions are as indicated.

`G = (n*m) H_ia = (k*n) H_ba = (k*m) u = size(H_ia,2); H = []; cvx_begin %quiet variable P(u,u) complex diagonal for t = 1:1:size(H_ia,1) H = [H; ((H_ia(t,:)*P*G) + H_ba(t,:))]; end maximize(lambda_sum_largest(H*H', size(H_ba,1))); subject to abs(diag(P)) == 1; cvx_end`

Upon running, CVX fails at H*H’ and returns the error message below. Can anyone help with that?

Error using * (line 126)

Disciplined convex programming error:

Only scalar quadratic forms can be specified in CVX