The Role of Regulatory in Price Control and Spectrum Allocation to Competing Wireless Access Networks

Document Type : Research Paper

Authors

1 Department of Computer Engineering, Amirkabir Universsity of Technology

2 department of Computer Engineering, Amirkabir Univ. of Technology

Abstract

With the rapid growth of wireless access networks, various providers offer their services using different technologies such as Wi-Fi, Wimax, 3G, 4G and so on. These networks compete for the scarce wireless spectrum. The spectrum is considered to be a scarce resource moderated by the spectrum allocation regulatory (“regulatory” for short) which is the governance body aiming to maximize the social welfare through moderation of the spectrum allocation table (SAT). In this paper, we present a three stage dynamic game model directed by the regulatory to maximize the clients' welfare. The regulatory controls the proposed prices announced by networks and it determines the tax in proportion to the price and load of each network. The model simulates the behavior of end users, network providers and the regulatory agent through which spectrum allocation strategy is deducted, the rules and parameters are defined, and the system equilibrium in terms of resource allocation and pricing is analyzed. The experimental results show that the proposed spectrum allocation schema results in a situation with the highest clients' welfare and network providers have enough advantages to stay in the market.

Keywords

References

[1]
E. Gustafsson and A. Jonsson, "Always best connected," IEEE Wireless Communication Magazin, vol. 10, no. 1, pp. 49-55, Feb. 2003.
[2]
J. W. Friedman, Oligopoly and the Theory of Games, vol. 8, North-Holland, 1977.
[3]
W. Wang, B. Liang and B. Li, "Designing truthful spectrum double auctions with local markets," IEEE Transactions Mobile Computing, vol. 13, no. 1, pp. 75-88, Jan. 2014.
[4]
M. Dong, G. Sun, X. Wang, and Q. Zhang, "Combinatorial auction with time-frequency flexibility in cognitive radio networks," INFOCOM, 2012 Proceedings IEEE, 2012.
[5]
Y. Chen, L. Duan, J. Huang, and Q. Zhang, "Balancing Income and User Utility in Spectrum Allocation," IEEE Transactions Mobile Computing, vol. 14, pp. 2460-2473, Dec. 2015.
[6]
D. Niyato and E. Hossain, "Competitive pricing in heterogeneous wireless access networks: Issues and approaches," IEEE Network, vol. 22, no. 6, pp. 4-11, Nov.-Dec. 2008.
[7]
O. Sallent, J. Pérez-Romero, R. Agusti, L. Giupponi, C. Kloeck, I. Martoyo, S. Klett, and J. Luo, "Resource auctioning mechanisms in heterogeneous wireless access networks,"Vehicular Technology Conference, 2006. VTC 2006-Spring. IEEE 63rd, 2006.
[8]
L. Duan, J. Huang, and B. Shou, "Optimal pricing for local and global WiFi markets," INFOCOM, 2013 Proceedings IEEE, 2013.
[9]
L. Duan, J. Huang, and B. Shou, "Pricing for Local and Global Wi-Fi Markets," IEEE Transactions Mobile Computing, vol. 14, no. 5, pp. 1056-1070, May 2015.
[10]
S. M. Matinkhah, S. Khorsandi, and S. Yarahmadian, "A load balancing system for autonomous connection management in heterogeneous wireless networks," Computer Communications, vol. 97, pp. 111-119, Jan. 2017.
[11]
J. Cao, J. Wu and W. Yang, "Spectrum allocation strategy for heterogeneous wireless service based on bidding game," KSII Transactions on Internet and Information Systems (TIIS), vol. 11, no. 3, pp. 1336-1356, March 2017.
[12]
J. Ramsay, "Purchasing power," European Journal of Purchasing & Supply Management, vol. 1, no. 3, pp. 125-138, Sept. 1994.
[13]
S. Schoenecker and T. Luginbuhl, "Characteristic Functions of the Product of Two Gaussian Random Variables and the Product of a Gaussian and a Gamma Random Variable," IEEE Signal Processing Letters, vol. 23, no. 5, pp. 644-647, May 2016.
[14]
N. O'Donoughue and J. M. Moura, "On the product of independent complex Gaussians," IEEE Transactions signal Processing, vol. 60, no. 3, pp. 1050-1063, March 2012.
[15]
A. Ribeiro, N. Medeiros, and N. Cota, "Comparison of GSM, WCDMA and LTE Performance on 900MHz Band," Procedia Technology, vol. 17, pp. 674-682, 2014.
[16]
H. W. Kuhn and A. W. Tucker, "Nonlinear programming," 2nd Berkeley Symposium. Berkeley, University of California Press, 1951.

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