  We study the trust-region subproblem (TRS) of minimizing a nonconvex
quadratic function over the unit ball with additional conic constraints.
Despite having a nonconvex objective, it is known that the classical TRS and a
number of its variants are polynomial-time solvable. In this paper, we follow a
second-order cone (SOC) based approach to derive an exact convex reformulation
of the TRS under a structural condition on the conic constraint. Our structural
condition is immediately satisfied when there is no additional conic
constraints, and it generalizes several such conditions studied in the
literature. As a result, our study highlights an explicit connection between
the classical nonconvex TRS and smooth convex quadratic minimization, which
allows for the application of cheap iterative methods such as Nesterov's
accelerated gradient descent, to the TRS. Furthermore, under slightly stronger
conditions, we give a low-complexity characterization of the convex hull of the
epigraph of the nonconvex quadratic function intersected with the constraints
defining the domain without any additional variables. We also explore the
inclusion of additional hollow constraints to the domain of the TRS, and
convexification of the associated epigraph.
