Technology Choices and Pricing Policies in Public and Private Wireless Networks

This paper studies the provision of a wireless network by a monopolistic provider who may be either benevolent (seeking to maximize social welfare, namely the sum utility of all the users) or selfish (seeking to maximize provider profit). The paper addresses the following questions: Under what circumstances is it feasible for a provider, either benevolent or selfish, to operate a network in such a way as to cover costs? How is the optimal behavior of a benevolent provider different from the optimal behavior of a selfish provider? And, most importantly, how does the medium access control (MAC) technology influence the answers to these questions? To address these questions, we build a general model, and provide analysis and simulations for simplified but typical scenarios; the focus in these scenarios is on the contrast between the outcomes obtained under carrier-sensing multiple access (CSMA) and outcomes obtained under time-division multiple access (TDMA). Simulation results demonstrate that differences in MAC technology can have a significant effect on social welfare, on provider profit, and even on the (financial) feasibility of a wireless network.

[1]  J. Nash NON-COOPERATIVE GAMES , 1951, Classics in Game Theory.

[2]  John N. Tsitsiklis,et al.  Efficiency of Scalar-Parameterized Mechanisms , 2008, Oper. Res..

[3]  Shuqin Li,et al.  Price Differentiation for Communication Networks , 2010, IEEE/ACM Transactions on Networking.

[4]  Jianwei Huang,et al.  Competition of Wireless Providers for Atomic Users , 2010, IEEE/ACM Transactions on Networking.

[5]  A. Mas-Colell,et al.  Microeconomic Theory , 1995 .

[6]  J. Walrand,et al.  WiFi access point pricing as a dynamic game , 2006, IEEE/ACM Transactions on Networking.

[7]  Julien Freudiger,et al.  On Wireless Social Community Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[8]  Mihaela van der Schaar,et al.  Optimized scalable video streaming over IEEE 802.11 a/e HCCA wireless networks under delay constraints , 2006, IEEE Transactions on Mobile Computing.

[9]  Keith W. Ross,et al.  The stochastic knapsack problem , 1989, IEEE Trans. Commun..

[10]  John N. Tsitsiklis,et al.  Efficiency loss in a network resource allocation game: the case of elastic supply , 2004, IEEE Transactions on Automatic Control.

[11]  Richard J. Gibbens,et al.  Resource pricing and the evolution of congestion control , 1999, at - Automatisierungstechnik.

[12]  Daniel Pérez Palomar,et al.  A tutorial on decomposition methods for network utility maximization , 2006, IEEE Journal on Selected Areas in Communications.

[13]  David Starobinski,et al.  Pricing strategies for spectrum lease in secondary markets , 2010, TNET.

[14]  Shaolei Ren,et al.  User subscription dynamics and revenue maximization in communications markets , 2011, 2011 Proceedings IEEE INFOCOM.

[15]  Shaolei Ren,et al.  Entry and Spectrum Sharing Scheme Selection in Femtocell Communications Markets , 2013, IEEE/ACM Transactions on Networking.

[16]  T. Basar,et al.  Differentiated Internet pricing using a hierarchical network game model , 2004, Proceedings of the 2004 American Control Conference.

[17]  Eitan Altman,et al.  Evolutionary Games in Wireless Networks , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[18]  Leonardo Badia,et al.  Resource Management in IEEE 802.11 Multiple Access Networks with Price-based Service Provisioning , 2008, IEEE Transactions on Wireless Communications.

[19]  Jinwoo Park,et al.  Price of Simplicity under Congestion , 2012, IEEE Journal on Selected Areas in Communications.

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

[21]  Shaolei Ren,et al.  User Subscription, Revenue Maximization, and Competition in Communications Markets , 2010, ArXiv.

[22]  David Starobinski,et al.  Spot pricing of secondary spectrum access in wireless cellular networks , 2009, TNET.

[23]  A. Girotra,et al.  Performance Analysis of the IEEE 802 . 11 Distributed Coordination Function , 2005 .

[24]  Marvin A. Sirbu,et al.  Evolving wireless access technologies for municipal broadband , 2006, Gov. Inf. Q..

[25]  Eric J. Friedman,et al.  Pricing WiFi at Starbucks: issues in online mechanism design , 2003, EC '03.

[26]  Dusit Niyato,et al.  Market-Equilibrium, Competitive, and Cooperative Pricing for Spectrum Sharing in Cognitive Radio Networks: Analysis and Comparison , 2008, IEEE Transactions on Wireless Communications.

[27]  Frank Kelly,et al.  Charging and rate control for elastic traffic , 1997, Eur. Trans. Telecommun..

[28]  Tamer Basar,et al.  Optimal Nonlinear Pricing for a Monopolistic Network Service Provider with Complete and Incomplete Information , 2007, IEEE Journal on Selected Areas in Communications.

[29]  Frank Kelly,et al.  Rate control for communication networks: shadow prices, proportional fairness and stability , 1998, J. Oper. Res. Soc..

[30]  David Starobinski,et al.  Online Pricing of Secondary Spectrum Access with Unknown Demand Function , 2012, IEEE Journal on Selected Areas in Communications.

[31]  R. Srikant,et al.  Revenue-maximizing pricing and capacity expansion in a many-users regime , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[32]  John N. Tsitsiklis,et al.  Congestion-dependent pricing of network services , 2000, TNET.

[33]  Shuqin Li,et al.  Revenue Maximization for Communication Networks with Usage-Based Pricing , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.