That error is because this is NOT an LMI due to the product term \lambda_0 X. It is a BMI (Bilinear Matrix Inequality), which is non-convex and will not be accepted by CVX. Why isn't CVX accepting my model? READ THIS FIRST!.
That said, I think you can solve this feasibility problem using the methods in section 4.2.5 “Quasiconvex optimization” in “Convex Optimization” by Boyd and Vandenberghe http://web.stanford.edu/~boyd/cvxbook/ . I leave you to work out the details.
Note that as a practical matter to deal with strict inequalities in the Corollary statement, and avoid the zero (singular for X) solution, you will need to use something like
X >= small_number_1*eye(n_x)
lambda0 >= small_number_2
mu1 > =small_number_3
where small_number_1, small_number_2, small_number3 are small positive numbers, which are very small, but larger than solver feasibility tolerance. So perhaps 1e-6 or 1e-5.