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Several gaps and errors in [1] are identified and corrected. Whileaccommodating these corrections, a rigours proof is given that the successiveconvex approximation algorithm in [1] for secrecy rate maximization (SRM) doesgenerate an increasing and bounded sequence of true secrecy rates and henceconverges. It is further shown that its convergence point is a KKT point of theoriginal SRM problem and, if the original problem is convex, this convergencepoint is globally-optimal, which is not necessarily the case in general. Aninterlacing property of the sequences of the true and approximate secrecy ratesis established.

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