  Consider an MISO channel overheard by multiple eavesdroppers. Our goal is to
design an artificial noise (AN)-aided transmit strategy, such that the
achievable secrecy rate is maximized subject to the sum power constraint.
AN-aided secure transmission has recently been found to be a promising approach
for blocking eavesdropping attempts. In many existing studies, the confidential
information transmit covariance and the AN covariance are not simultaneously
optimized. In particular, for design convenience, it is common to prefix the AN
covariance as a specific kind of spatially isotropic covariance. This paper
considers joint optimization of the transmit and AN covariances for secrecy
rate maximization (SRM), with a design flexibility that the AN can take any
spatial pattern. Hence, the proposed design has potential in jamming the
eavesdroppers more effectively, based upon the channel state information (CSI).
We derive an optimization approach to the SRM problem through both analysis and
convex conic optimization machinery. We show that the SRM problem can be recast
as a single-variable optimization problem, and that resultant problem can be
efficiently handled by solving a sequence of semidefinite programs. Our
framework deals with a general setup of multiple multi-antenna eavesdroppers,
and can cater for additional constraints arising from specific application
scenarios, such as interference temperature constraints in interference
networks. We also generalize the framework to an imperfect CSI case where a
worst-case robust SRM formulation is considered. A suboptimal but safe solution
to the outage-constrained robust SRM design is also investigated. Simulation
results show that the proposed AN-aided SRM design yields significant secrecy
rate gains over an optimal no-AN design and the isotropic AN design, especially
when there are more eavesdroppers.
