  Several gaps and errors in [1] are identified and corrected. While
accommodating these corrections, a rigours proof is given that the successive
convex approximation algorithm in [1] for secrecy rate maximization (SRM) does
generate an increasing and bounded sequence of true secrecy rates and hence
converges. It is further shown that its convergence point is a KKT point of the
original SRM problem and, if the original problem is convex, this convergence
point is globally-optimal, which is not necessarily the case in general. An
interlacing property of the sequences of the true and approximate secrecy rates
is established.
