  This paper considers artificial noise (AN)-aided transmit designs for
multi-user MISO systems in the eyes of service integration. Specifically, we
combine two sorts of services, and serve them simultaneously: one multicast
message intended for all receivers and one confidential message intended for
only one receiver. The confidential message is kept perfectly secure from all
the unauthorized receivers. Our goal is to jointly design the optimal input
covariances for the multicast message, confidential message and AN, such that
the achievable secrecy rate region is maximized subject to the sum power
constraint. This secrecy rate region maximization (SRRM) problem is a nonconvex
vector maximization problem. To handle it, we reformulate the SRRM problem into
a provably equivalent scalar optimization problem and propose a searching
method to find all of its Pareto optimal points. The equivalent scalar
optimization problem is identified as a secrecy rate maximization (SRM) problem
with the quality of multicast service (QoMS) constraints. Further, we show that
this equivalent QoMS-constrained SRM problem, albeit nonconvex, can be
efficiently handled based on a two-stage optimization approach, including
solving a sequence of semidefinite programs. Moreover, we also extend the SRRM
problem to an imperfect channel state information (CSI) case where a worst-case
robust formulation is considered. In particular, while transmit beamforming is
generally a suboptimal technique to the SRRM problem, we prove that it is
optimal for the confidential message transmission whether in the perfect CSI
scenario or in the imperfect CSI scenario. Finally, numerical results
demonstrate that the AN-aided transmit designs are effective in expanding the
achievable secrecy rate regions.
