  Conventional multi-user scheduling schemes are designed based on
instantaneous channel state information (CSI), indicating that decisions must
be made every transmission time interval (TTI) which lasts at most several
milliseconds. Only quite simple approaches can be exploited under this
stringent time constraint, resulting in less than satisfactory scheduling
performance. In this paper, we investigate the scheduling problem of a fixed
wireless access (FWA) network using only statistical CSI. Thanks to their fixed
positions, user terminals in FWA can easily provide reliable large-scale CSI
lasting tens or even hundreds of TTIs. Inspired by this appealing fact, we
propose an \emph{`once-and-for-all'} scheduling approach, i.e. given multiple
TTIs sharing identical statistical CSI, only a single high-quality scheduling
decision lasting across all TTIs shall be taken rather than repeatedly making
low-quality decisions every TTI. The proposed scheduling design is essentially
a mixed-integer non-smooth non-convex stochastic problem with the objective of
maximizing the weighted sum rate as well as the number of active users. We
firstly replace the indicator functions in the considered problem by
well-chosen sigmoid functions to tackle the non-smoothness. Via leveraging
deterministic equivalent technique, we then convert the original stochastic
problem into an approximated deterministic one, followed by linear relaxation
of the integer constraints. However, the converted problem is still highly
non-convex due to implicit equation constraints introduced by deterministic
equivalent. To address this issue, we employ implicit optimization technique so
that the gradient can be derived explicitly, with which we propose an algorithm
design based on accelerated Frank-Wolfe method. Numerical results verify the
effectiveness of our proposed scheduling scheme over state-of-the-art.
