  The security of spatial modulation (SM) aided networks can always be improved
by reducing the desired link's power at the cost of degrading its bit error
ratio performance and assuming the power consumed to artificial noise (AN)
projection (ANP). We formulate the joint optimization problem of maximizing the
secrecy rate (Max-SR) over the transmit antenna selection and ANP in the
context of secure SM-aided networks, which is mathematically a non-linear mixed
integer programming problem. In order to solve this problem, we provide a pair
of solutions, namely joint and separate solutions. Specifically, an accurate
approximation of the SR is used for reducing the computational complexity, and
the optimal AN covariance matrix (ANCM) is found by convex optimization for any
given active antenna group (AAG). Then, given a large set of AAGs, simulated
annealing mechanism is invoked for optimizing the choice of AAG, where the
corresponding ANCM is recomputed by this optimization method as well when the
AAG changes. To further reduce the complexity of the above-mentioned joint
optimization, a low-complexity two-stage separate optimization method is also
proposed. Furthermore, when the number of transmit antennas tends to infinity,
the Max-SR problem becomes equivalent to that of maximizing the ratio of the
desired user's signal-to-interference-plus-noise ratio to the eavesdropper's.
Thus our original problem reduces to a fractional programming problem, hence a
significant computational complexity reduction can be achieved for the
optimization problem. Our simulation results show that the proposed algorithms
outperform the existing leakage-based null-space projection scheme in terms of
the SR performance attained, and drastically reduces the complexity at a slight
SR performance reduction.
