  Next generation wireless architectures are expected to enable slices of
shared wireless infrastructure which are customized to specific mobile
operators/services. Given infrastructure costs and the stochastic nature of
mobile services' spatial loads, it is highly desirable to achieve efficient
statistical multiplexing amongst such slices. We study a simple dynamic
resource sharing policy which allocates a 'share' of a pool of (distributed)
resources to each slice-Share Constrained Proportionally Fair (SCPF). We give a
characterization of SCPF's performance gains over static slicing and general
processor sharing. We show that higher gains are obtained when a slice's
spatial load is more 'imbalanced' than, and/or 'orthogonal' to, the aggregate
network load, and that the overall gain across slices is positive. We then
address the associated dimensioning problem. Under SCPF, traditional network
dimensioning translates to a coupled share dimensioning problem, which
characterizes the existence of a feasible share allocation given slices'
expected loads and performance requirements. We provide a solution to robust
share dimensioning for SCPF-based network slicing. Slices may wish to
unilaterally manage their users' performance via admission control which
maximizes their carried loads subject to performance requirements. We show this
can be modeled as a 'traffic shaping' game with an achievable Nash equilibrium.
Under high loads, the equilibrium is explicitly characterized, as are the gains
in the carried load under SCPF vs. static slicing. Detailed simulations of a
wireless infrastructure supporting multiple slices with heterogeneous mobile
loads show the fidelity of our models and range of validity of our high load
equilibrium analysis.
