The analysis of the techno-economic interactions among the mobile operators and tenants (slices) in the context of 5G network slicing has lately received growing interest by the research community. In particular the problems of admission control, resource allocation/scheduling and pricing for network slicing are not trivial as they affect the profits of the involved stakeholders such as the operator (slice provider) and the network slice owners (tenants or service providers) and therefore the viability of the slice market. Since such problems are entwined, we propose here a novel optimization framework that jointly addresses admission control, resource allocation and pricing. In the proposed framework, the operator owns a fixed amount of resources whereas each slice is characterized by a stochastic demand and utility function reflecting its Quality of Service (QoS) requirements. We have considered two types of slices, one with low traffic profile and deterministic QoS, representing Ultra Reliable Low Latency Communications (URLLC), and one with higher traffic profile and statistical QoS, representing enhanced Mobile BroadBand (eMBB). We devise several models based on whether we allow statistical multiplexing and whether we make use of different prices for different types of slices. We also evaluate the impact of the description of traffic in an aggregate way compared to a detailed one. The outcomes of all variants are analyzed through some numerical experiments which enable us to assess the main flavors of each model.

The rapid evolution of mobile radio network technologies poses severe technical and economical challenges to mobile network operators (MNOs); on the economical side, the continuous roll-out of technology updates is highly expensive, which may lead to the extreme, where offering advanced mobile services becomes no longer affordable for MNOs which thus, are not incentivized to innovate. Mobile infrastructure sharing among MNOs becomes then an important building block to lower the required per-MNO investment cost involved in the technology roll-out and management phases. We focus on a radio access network (RAN) sharing situation where multiple MNOs with a consolidated network infrastructure coexist in a given set of geographical areas; the MNOs have then to decide if it is profitable to upgrade their RAN technology by deploying additional small-cell base stations and whether to share the investment (and the deployed infrastructure) of the new small-cells with other operators. We address such strategic problems by giving a mathematical framework for the RAN infrastructure sharing problem which returns the “best” infrastructure sharing strategies for operators (coalitions and network configuration) when varying techno-economic parameters such as the achievable throughput in different sharing configurations and the pricing models for the service offered to the users. The proposed formulation is then leveraged to analyze the impact of the aforementioned parameters/input in a realistic mobile network environment based on LTE technology.

To accommodate the ever-growing traffic load and bandwidth demand generated by mobile users, mobile network operators (MNOs) need to frequently invest in high spectral efficiency technologies and increase their hold of spectrum resources; MNOs have then to weigh between building individual networks or entering into network and spectrum sharing agreements. We address here the problem of radio access network and spectrum sharing in 4G mobile networks by focusing on a case when multiple MNOs plan to deploy small cell base stations in a geographical area in order to upgrade their existing network infrastructure. We propose two cooperative game models (with and without transferable utility) to address the proposed problem: for given network (user throughput, MNO market, and spectrum shares) and economic (coalition cost and mobile data pricing model) settings, the proposed models output a cost division policy that guarantees coalition (sharing agreement) stability.

This work considers the strategic situation which arises when Mobile Network Operators (MNOs) coexisting in a given geographical area have to decide whether to invest in new radio access technology and whether to share the investment (and the infrastructure) with other operators. We focus on heterogeneous networks (HetNet) where MNOs add a layer of small cells to their existing macro cells. We address such strategic scenario by proposing a Mixed Integer Linear Programming formulation of the infrastructure sharing problem which takes as input techno-economic parameters as the achievable throughput in different sharing configurations, the pricing models for the service offered to the end users and the expectations on the return on investment for the mobile operators, and returns as output the “best” infrastructure/investment sharing options for the MNOs. The proposed formulation is finally leveraged to analyze the dynamics involved in the infrastructure sharing process under different techno-economic conditions in realistic network scenarios.