On Optimal Orchestration of Virtualized Cellular Networks With Statistical Multiplexing

Wireless network virtualization is emerging as a promising technology for cellular networks. A key advantage of introducing virtualization in cellular networks is that wireless services can be decoupled from network resources (e.g., infrastructure and spectrum) so that multiple virtual networks can be built using a shared pool of network resources. This paper develops an optimization framework for orchestrating virtualized cellular networks while enabling and exploiting statistical multiplexing. Our proposed framework has two phases: virtual network deployment (static) and statistical multiplexing (adaptive). In the virtual network deployment phase, network resources are aggregated, sliced, and allocated to the virtual networks considering the presence of uncertainty in user equipment (UE) locations and channel conditions, without knowing which realization of UE locations and channel conditions will occur. Once the virtual networks are deployed, each of the aggregated base stations (BSs) performs statistical multiplexing, i.e., allocates excess resources from the over-satisfied slices to the under-satisfied slices, according to the realized channel conditions of associated UEs. Our numerical results demonstrate that the proposed framework outperforms existing virtualization frameworks in terms of probabilistically satisfying virtual networks’ rate and coverage demands while minimizing resource over-provisioning, in the presence of uncertainty in UE locations and channel conditions.