How to deal with the error" Cannot perform the operation: {concave} .* {complex affine}"

There is something wrong with the code line with “T = [W * F(:,:,j), sigma * W, sigma_z * U]';
Did I correctly write the code line:”sigma_z = sqrt( (P_max - square_pos(norm(OBJ,'fro')))/(M - K));”?
How to deatl with this problem?

clear;

num_CSI = 1;
P_max = 10; % dB
P_max = 10 ^ (P_max / 10); % the true total power
M = 4; % number of relays
K = 2; % number of S-D pair
gama = 0.3; % MSE target
sigma = sqrt(0.1); % noise variance
epsilon = 0.1; % norm-bounded
j = 1;
 while (j <= num_CSI)
   F(:,:,j) = (randn(M,K) + sqrt(-1) * randn(M,K)) / sqrt(2); %
   G(:,:,j) = (randn(M,K) + sqrt(-1) * randn(M,K)) / sqrt(2);
   j = j + 1;
 end
 I = eye(K);
for j =1:1 

  [U_svd S_svd V_svd] = svd(G(:,:,j)');
  U = V_svd(:,(K+1):M);
 
  cvx_begin sdp quiet  
      cvx_solver sedumi
      variable W(M,M) complex;
      variable mu;
      variable lambda(K);
      expression c(2*M,1);
      expression T(2*M,M);
      expression sigma_z;
      expression OBJ(M,M + K);
             
      minimize(mu);  % object function
      subject to
      OBJ = [W * F(:,:,j), sigma * W];
      sigma_z = sqrt( (P_max - square_pos(norm(OBJ,'fro')))/(M - K));%vec(OBJ)      
      for k = 1:K
          c = [G(:,k,j)' * W * F(:,:,j) - I(k,:), sigma * G(:,k,j)' * W, zeros(1,(M-K))]';
          T = [W * F(:,:,j), sigma * W, sigma_z * U]';%
          [gama - sigma^2 - lambda(k), c', zeros(1,M); 
           c, eye(2*M,2*M), -epsilon * T;
           zeros(M,1),-epsilon * T', lambda(k) * eye(M,M);] >= 0; 
          lambda(k) >= 0;
      end
      norm(OBJ,'fro') <= sqrt(mu); 
  cvx_end
  if strfind(cvx_status,'Solved')
     pow = mu
     WW = W
  end 
end

First question: is your problem convex?

I want to get the optimal matrix W. But I am not sure whether it can be resolved.
Note that W,\mu,\lambda_{1},\ldots,\lambda_{K} are variables, others are fixed.
Is it convex or quasiconvex or nonconvex? How can I solve it?
image description

This really isn’t the right forum to ask for modeling advice, I’m afraid—this is specifically for issues with CVX. If you haven’t yet determined convexity, then you’re not a CVX user yet, because CVX is for modeling problems that you already know are convex.