  An important aspect of 5G networks is the development of Radio Access Network
(RAN) slicing, a concept wherein the virtualized infrastructure of wireless
networks is subdivided into slices (or enterprises), tailored to fulfill
specific use-cases. A key focus in this context is the efficient radio resource
allocation to meet various enterprises' service-level agreements (SLAs). In
this work, we introduce a channel-aware and SLA-aware RAN slicing framework for
massive multiple input multiple output (MIMO) networks where resource
allocation extends to incorporate the spatial dimension available through
beamforming. Essentially, the same time-frequency resource block (RB) can be
shared across multiple users through multiple antennas. Notably, certain
enterprises, particularly those operating critical infrastructure, necessitate
dedicated RB allocation, denoted as private networks, to ensure security.
Conversely, some enterprises would allow resource sharing with others in the
public network to maintain network performance while minimizing capital
expenditure. Building upon this understanding, the proposed scheduler comprises
scheduling schemes under both scenarios: where different slices share the same
set of RBs, and where they require exclusivity of allocated RBs. We validate
the efficacy of our proposed schedulers through simulation by utilizing a
channel data set collected from a real-world massive MIMO testbed. Our
assessments demonstrate that resource sharing across slices using our approach
can lead up to 60.9% reduction in RB usage compared to other approaches.
Moreover, our proposed schedulers exhibit significantly enhanced operational
efficiency, with significantly faster running time compared to exhaustive
greedy approaches while meeting the stringent 5G sub-millisecond-level latency
requirement.
