Mobile network operators are facing the difficult task of significantly increasing capacity to meet projected demand while keeping CAPEX and OPEX down. We argue that infrastructure sharing is a key consideration in operators' planning of the evolution of their networks, and that such planning can be viewed as a stage in the cognitive cycle. In this paper, we present a framework to model this planning process while taking into account both the ability to share resources and the constraints imposed by competition regulation (the latter quantified using the Herfindahl index). Using real-world demand and deployment data, we find that the ability to share infrastructure essentially moves capacity from rural, sparsely populated areas (where some of the current infrastructure can be decommissioned) to urban ones (where most of the next-generation base stations would be deployed), with significant increases in resource efficiency. Tight competition regulation somewhat limits the ability to share but does not entirely jeopardize those gains, while having the secondary effect of encouraging the wider deployment of next-generation technologies.
Works such as @cite_9 focus on economic aspects of resource sharing from a network virtualization perspective. It describes the incentives operators have to pool their resources together. From an implementation perspective, the analysis of cooperative sharing arrangements presented in @cite_5 highlights the diversity of approaches currently being used in existing networks, their successes and failures. It points to a process of learning within industry as to which sharing modes allow for both competition and cooperative sharing to thrive. A study of Pakistan's experience of network sharing indicates the varying economic gains made in a still-developing market by adopting different sharing strategies @cite_20 .
@cite_5 @cite_9 @cite_20
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This paper address issues about cooperation among and competition between mobile network operators. The starting point is to examine why and how operators share infrastructure for mobile communication services, so called network sharing. The paper analyzes drivers, benefits and obstacles of network cooperation. We also analyze how roles and responsibilities are distributed for the network related functions while concurrently operators compete for customers and have separate functionality for service provisioning, marketing, customer relation management, charging and billing. Next, we analyze how network sharing as such and strategies for network sharing have changed in Sweden from the year 2000 when the 3G licenses were awarded and up to the year 2010. Moreover, network sharing in Sweden is compared with India where the market situation is different, as the number of operators is four times more and the cooperation is organized in another way, with separate tower companies, which provides base stations sites where operators are tenants. Finally, we compare the network sharing cases with how mobile operators organize cooperation for mobile payments services. From our empirical data we can identify four different types of co-opetition among mobile operators. 1. A co-operative spirit with focus on working practices and or principles that will facilitate the common use of resources or solutions. 2. Infrastructure cooperation through a third party, e.g. a tower company or a SMS aggregator with the main objective to reduce costs or to provide a common solution. The operators have agreements with a third party but not with each other. 3. Infrastructure cooperation through a joint venture that is responsible for network deployment and operation. The driver is to achieve cost-savings. The operators have their own service provisioning, billing, customer relations management and compete for end-users. 4. Service and infrastructure cooperation through a joint venture that is fully responsible for providing the end-user service, in our case mobile payments. The main driver is to offer a payment solution common for all operators in order to complement or compete with solutions provided by banks or payment service providers. This paper presents a novel economic model to regulate capacity sharing in a federation of hybrid cloud providers (CPs). The proposed work models the interactions among the CPs as a repeated game among selfish players that aim at maximizing their profit by selling their unused capacity in the spot market but are uncertain of future workload fluctuations. The proposed work first establishes that the uncertainty in future revenue can act as a participation incentive to sharing in the repeated game. We, then, demonstrate how an efficient sharing strategy can be obtained via solving a simple dynamic programming problem. The obtained strategy is a simple update rule that depends only on the current workloads and a single variable summarizing past interactions. In contrast to existing approaches, the model incorporates historical and expected future revenue as part of the virtual machine (VM) sharing decision. Moreover, these decisions are not enforced neither by a centralized broker nor by predefined agreements. Rather, the proposed model employs a simple grim trigger strategy where a CP is threatened by the elimination of future VM hosting by other CPs. Simulation results demonstrate the performance of the proposed model in terms of the increased profit and the reduction in the variance in the spot market VM availability and prices. Resource sharing among mobile network operators is a promising way to tackle growing data demand by increasing capacity and reducing costs of network infrastructure deployment and operation. In this work, we evaluate sharing options that range from simple approaches that are feasible in the near-term on traditional infrastructure to complex methods that require specialized virtualized infrastructure. We build a simulation testbed supporting two geographically overlapped 4G LTE macro cellular networks and model the sharing architecture process between the network operators. We compare Capacity Sharing (CS) and Spectrum Sharing (SS) on traditional infrastructure and Virtualized Spectrum Sharing (VSS) and Virtualized PRB Sharing (VPS) on virtualized infrastructure under light, moderate and heavy user loading scenarios in collocated and noncollocated E-UTRAN deployment topologies. We also study these sharing options in conservative and aggressive sharing participation modes. Based on simulation results, we conclude that CS, a generalization of traditional roaming, is the best performing and simplest option, SS is least effective and that VSS and VPS perform better than spectrum sharing with added complexity. Fragmentation of expensive resources, e.g., spectrum for wireless services, between providers can introduce inefficiencies in resource utilisation and worsen overall system performance. In such cases, resource pooling between independent service providers can be used to improve performance. However, for providers to agree to pool their resources, the arrangement has to be mutually beneficial. The traditional notion of resource pooling, which implies complete sharing, need not have this property. For example, under full pooling, one of the providers may be worse off and hence have no incentive to participate. In this paper, we propose partial resource sharing models as a generalization of full pooling, which can be configured to be beneficial to all participants. We formally define and analyze two partial sharing models between two service providers, each of which is an Erlang-B loss system with the blocking probabilities as the performance measure. We show that there always exist partial sharing configurations that are beneficial to both providers, irrespective of the load and the number of circuits of each of the providers. A key result is that the Pareto frontier has at least one of the providers sharing all its resources with the other. Furthermore, full pooling may not lie inside this Pareto set. The choice of the sharing configurations within the Pareto set is formalized based on bargaining theory. Finally, large system approximations of the blocking probabilities in the quality-efficiency-driven regime are presented.