  To tackle the challenge of providing higher data rates within limited
spectral resources we consider the case of multiple operators sharing a common
pool of radio resources. Four algorithms are proposed to address co-primary
multi-operator radio resource sharing under heterogeneous traffic in both
centralized and distributed scenarios. The performance of these algorithms is
assessed through extensive system-level simulations for two indoor small cell
layouts. It is assumed that the spectral allocations of the small cells are
orthogonal to the macro network layer and thus, only the small cell traffic is
modeled. The main performance metrics are user throughput and the relative
amount of shared spectral resources. The numerical results demonstrate the
importance of coordination among co-primary operators for an optimal resource
sharing. Also, maximizing the spectrum sharing percentage generally improves
the achievable throughput gains over non-sharing.
