  Massive multiple-input multiple-output communications can achieve high-level
security by concentrating radio frequency signals towards the legitimate users.
However, this system is vulnerable in a Rician fading environment if the
eavesdropper positions itself such that its channel is highly "similar" to the
channel of a legitimate user. To address this problem, this paper proposes an
angle aware user cooperation (AAUC) scheme, which avoids direct transmission to
the attacked user and relies on other users for cooperative relaying. The
proposed scheme only requires the eavesdropper's angle information, and adopts
an angular secrecy model to represent the average secrecy rate of the attacked
system. With this angular model, the AAUC problem turns out to be nonconvex,
and a successive convex optimization algorithm, which converges to a
Karush-Kuhn-Tucker solution, is proposed. Furthermore, a closed-form solution
and a Bregman first-order method are derived for the cases of large-scale
antennas and large-scale users, respectively. Extension to the intelligent
reflecting surfaces based scheme is also discussed. Simulation results
demonstrate the effectiveness of the proposed successive convex optimization
based AAUC scheme, and also validate the low-complexity nature of the proposed
large-scale optimization algorithms.
