Modeling the Techno-Economic Interactions of Infrastructure and Service Providers in 5G Networks With a Multi-Leader-Follower Game

The decoupling of infrastructure from services, which has been so far a mainstream paradigm in the computational and storage domain, is now becoming a paradigm also for mobile networks. Indeed, 5G must provide a variety of services with very diverse requirements, such as throughput, latency, or reliability, and decoupling infrastructure from service provisioning allows to deal with such heterogeneity. In this context, a new business model, involving two different stakeholders, Infrastructure Providers and Service Providers, has emerged. Besides addressing the technical issues, it is also important to study the economic feasibility and behavior of such new paradigm and the techno-economic interactions among the different stakeholders that play different roles in the mobile network market. In this paper, we propose a multi-leader multi-follower variant of the Stackelberg game to model the considered environment. The proposed model is then fed with realistic data and used to analyze the system behavior and the impact of the technological features of the stakeholders on their competitiveness.

[1]  David Hutchison,et al.  Game Theory for Multi-Access Edge Computing: Survey, Use Cases, and Future Trends , 2017, IEEE Communications Surveys & Tutorials.

[2]  Tommaso Melodia,et al.  Low-Complexity Distributed Radio Access Network Slicing: Algorithms and Experimental Results , 2018, IEEE/ACM Transactions on Networking.

[3]  Chih-Yu Wang,et al.  Incentive Compatible Overlay D2D System: A Group-Based Framework without CQI Feedback , 2018, IEEE Transactions on Mobile Computing.

[4]  Heinrich von Stackelberg Market Structure and Equilibrium , 2010 .

[5]  Zhu Han,et al.  A Stackelberg Game Approach to Proactive Caching in Large-Scale Mobile Edge Networks , 2018, IEEE Transactions on Wireless Communications.

[6]  Zhu Han,et al.  Applications of Economic and Pricing Models for Resource Management in 5G Wireless Networks: A Survey , 2017, IEEE Communications Surveys & Tutorials.

[7]  Walid Saad,et al.  Toward Massive Machine Type Cellular Communications , 2017, IEEE Wireless Communications.

[8]  Yang Zhang,et al.  Virtualization of 5G Cellular Networks: A Combinatorial Double Auction Approach , 2017, GLOBECOM 2017 - 2017 IEEE Global Communications Conference.

[9]  A. S. Madhukumar,et al.  Stackelberg Bayesian Game for Power Allocation in Two-Tier Networks , 2016, IEEE Transactions on Vehicular Technology.

[10]  Carlo Bellettini SISTEMI PER LA MOBILITÀ DEGLI UTENTI E DEGLIAPPLICATIVI IN RETI WIRED E WIRELESS , 2010 .

[11]  Leonardo Badia,et al.  Demand and pricing effects on the radio resource allocation of multimedia communication systems , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[12]  Choong Seon Hong,et al.  Dynamic pricing for resource allocation in wireless network virtualization: A Stackelberg game approach , 2017, 2017 International Conference on Information Networking (ICOIN).

[13]  Masao Fukushima,et al.  Quasi-variational inequalities, generalized Nash equilibria, and multi-leader-follower games , 2005, Comput. Manag. Sci..

[14]  Leonardo Badia,et al.  On utility-based radio resource management with and without service guarantees , 2004, MSWiM '04.

[15]  Leonardo Badia,et al.  An optimization framework for radio resource management based utility vs. price tradeoff in WCDMA systems , 2005, Third International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt'05).

[16]  Tapani Ristaniemi,et al.  Service provisioning with multiple service providers in 5G ultra-dense small cell networks , 2015, 2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[17]  Walid Saad,et al.  Pricing in Heterogeneous Wireless Networks: Hierarchical Games and Dynamics , 2014, IEEE Transactions on Wireless Communications.

[18]  Min Sheng,et al.  Wireless Service Provider Selection and Bandwidth Resource Allocation in Multi-Tier HCNs , 2016, IEEE Transactions on Communications.

[19]  Dusit Niyato,et al.  Pricing and Rate Optimization of Cloud Radio Access Network Using Robust Hierarchical Dynamic Game , 2017, IEEE Transactions on Wireless Communications.

[20]  E. Oughton,et al.  The cost, coverage and rollout implications of 5G infrastructure in Britain , 2017, Telecommunications Policy.

[21]  Leonardo Badia,et al.  Pricing VoWLAN services through a micro-economic framework , 2006, IEEE Wireless Communications.

[22]  M. Zorzi,et al.  An analysis of multimedia services in next generation communication systems with QoS and revenue management , 2004, 2004 IEEE 59th Vehicular Technology Conference. VTC 2004-Spring (IEEE Cat. No.04CH37514).

[23]  Masao Fukushima,et al.  Quasi-variational inequalities, generalized Nash equilibria, and multi-leader-follower games , 2009, Comput. Manag. Sci..

[24]  Dusit Niyato,et al.  A game theoretic analysis of service competition and pricing in heterogeneous wireless access networks , 2008, IEEE Transactions on Wireless Communications.

[25]  Kun Zhu,et al.  Virtualization of 5G Cellular Networks as a Hierarchical Combinatorial Auction , 2015, IEEE Transactions on Mobile Computing.

[26]  Rongbo Zhu,et al.  Dynamic Spectrum Access Algorithm Based on Game Theory in Cognitive Radio Networks , 2015, Mob. Networks Appl..

[27]  Vincenzo Sciancalepore,et al.  From network sharing to multi-tenancy: The 5G network slice broker , 2016, IEEE Communications Magazine.

[28]  Yang Jia,et al.  Bankruptcy game based resource allocation algorithm for 5G Cloud-RAN slicing , 2018, 2018 IEEE Wireless Communications and Networking Conference (WCNC).