Base station selection in two-tier femtocell networks: A game-theoretic approach
Subject Areas :
Statistics
Azadeh Pourkabirian
1
,
Mehdi Dehghan Takht Fooladi
2
,
Esmaeil Zeinali
3
,
Amir Masoud Rahmani
4
1 - Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2 - Department of Computer Engineering and Information Technology, Amirkabir University of Technology, Tehran, Iran
3 - Department of Computer and Information Technology Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
4 - Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Received: 2018-11-12
Accepted : 2019-01-19
Published : 2021-09-23
Keywords:
کیفیت سرویس,
الگوریتم یادگیریEXP3,
نظریه بازی تکاملی,
تخصیص منابع,
شبکههای بیسیم دو-ردهای فمتوسل,
Abstract :
Resource allocation has always been one of the main challenges in the design of wireless cellular networks. Suitable resource allocation, more specifically that includes suitable base station selection and bandwidth allocation can play an effective role in interference mitigation and users’ quality of service requirement satisfaction. In this paper, a game theoretic approach is proposed to solve the BS selection problem in two-tier wireless femtocell networks. We formulate the competitive behavior of users as evolutionary game theory. We calculate the probability of a user choosing a BS, compute the cell load of each BS, and analyze the demand rejection probability of the user associated with the BS. The proposed approach maximizes network throughput as well as meeting the QoS requirements of the users. Finally, we propose a decentralized learning algorithm based on EXP3 algorithm to achieve the evolutionary equilibrium as the solution of the game. Simulation results show that the proposed approach achieves a desirable performance and guarantees users’ QoS requirements.
References:
“Wifi and femtocell integration strategies 2011-2015,” Juniper Research Whitepaper, http://www.juniperresearch.com/, Mar. 2011.
Saquib, N., Hossain, E. and Kim, D.I., 2013. Fractional frequency reuse for interference management in LTE-advanced hetnets. IEEE Wireless Communications, 20(2), pp.113-122.
Jin, F., Zhang, R. and Hanzo, L., 2013. Fractional frequency reuse aided twin-layer femtocell networks: Analysis, design and optimization. IEEE Transactions on Communications, 61(5), pp.2074-2085.
Jeon, W.S., Kim, J. and Jeong, D.G., 2013. Downlink radio resource partitioning with fractional frequency reuse in femtocell networks. IEEE Transactions on Vehicular Technology, 63(1), pp.308-321.
Torregoza, J., Enkhbat, R. and Hwang, W.J., 2010. Joint power control, base station assignment, and channel assignment in cognitive femtocell networks. EURASIP Journal on wireless communications and networking, 2010, pp.1-14.
Chandrasekhar, V. and Andrews, J.G., 2009. Spectrum allocation in tiered cellular networks. IEEE Transactions on Communications, 57(10), pp.3059-3068.
Liu, D., Zhang, H., Zheng, W. and Wen, X., 2012, October. The sub-channel allocation algorithm in femtocell networks based on ant colony optimization. In MILCOM 2012-2012 IEEE Military Communications Conference (pp. 1-6). IEEE.
Xu, C., Sheng, M., Wang, X., Wang, C.X. and Li, J., 2014. Distributed subchannel allocation for interference mitigation in OFDMA femtocells: A utility-based learning approach. IEEE Transactions on Vehicular Technology, 64(6), pp.2463-2475.
Uygungelen, S., Auer, G. and Bharucha, Z., 2011, May. Graph-based dynamic frequency reuse in femtocell networks. In 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring) (pp. 1-6). IEEE.
Widiarti, H., Pyun, S.Y. and Cho, D.H., 2010, September. Interference mitigation based on femtocells grouping in low duty operation. In 2010 IEEE 72nd Vehicular Technology Conference-Fall (pp. 1-5). IEEE.
Kim, K., Han, Y. and Kim, S.L., 2005. Joint subcarrier and power allocation in uplink OFDMA systems. IEEE Communications Letters, 9(6), pp.526-528.
u, D., Yu, D. and Cai, Y., 2008, June. Subcarrier and power allocation in uplink OFDMA systems based on game theory. In 2008 international conference on neural networks and signal processing (pp. 522-526). IEEE.
Wu, D., Yu, D. and Cai, Y., 2008, June. Subcarrier and power allocation in uplink OFDMA systems based on game theory. In 2008 international conference on neural networks and signal processing (pp. 522-526). IEEE.
Wong, C.Y., Tsui, C.Y., Cheng, R.S. and Letaief, K.B., 1999, September. A real-time sub-carrier allocation scheme for multiple access downlink OFDM transmission. In Gateway to 21st Century Communications Village. VTC 1999-Fall. IEEE VTS 50th Vehicular Technology Conference (Cat. No. 99CH36324) (Vol. 2, pp. 1124-1128). IEEE.
Pietrzyk, S. and Janssen, G.J., 2002, September. Multiuser subcarrier allocation for QoS provision in the OFDMA systems. In Proceedings IEEE 56th vehicular technology conference (Vol. 2, pp. 1077-1081). IEEE.
Estrada, R., Jarray, A., Otrok, H. and Dziong, Z., 2014. Base station selection and resource allocation in macro–femtocell networks under noisy scenario. Wireless networks, 20(1), pp.115-131.
Barbarossa, S., Carfagna, A., Sardellitti, S., Omilipo, M. and Pescosolido, L., 2011, May. Optimal radio access in femtocell networks based on Markov modeling of interferers' activity. In 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 3212-3215). IEEE.
Huang, J., Subramanian, V.G., Agrawal, R. and Berry, R., 2009. Joint scheduling and resource allocation in uplink OFDM systems for broadband wireless access networks. IEEE Journal on Selected Areas in Communications, 27(2), pp.226-234.
Ha, V.N. and Le, L.B., 2013. Fair resource allocation for OFDMA femtocell networks with macrocell protection. IEEE transactions on vehicular technology, 63(3), pp.1388-1401.
Liang, Y.S., Chung, W.H., Ni, G.K., Chen, Y., Zhang, H. and Kuo, S.Y., 2012. Resource allocation with interference avoidance in OFDMA femtocell networks. IEEE Transactions on Vehicular Technology, 61(5), pp.2243-2255.
Guvenc, I., Jeong, M.R., Watanabe, F. and Inamura, H., 2008. A hybrid frequency assignment for femtocells and coverage area analysis for co-channel operation. IEEE Communications Letters, 12(12), pp.880-882.
Giupponi, L. and Ibars, C., 2010, September. Distributed interference control in OFDMA-based femtocells. In 21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 1201-1206. IEEE.
Kim, B.G., Kwon, J.A. and Lee, J.W., 2011, July. Utility-based subchannel allocation for OFDMA femtocell networks. In 2011 Proceedings of 20th International Conference on Computer Communications and Networks (ICCCN), pp. 1-6. IEEE.
FALLAH, M.O., SHAHGHOLI, G.B., Mala, H. and MOVAHEDINIA, N., 2014. Demand based Resource Allocation to Balance the Utilization and User Level Fairness in Femtocell Networks, PP.187-204.
Mittal, K., Belding, E.M. and Suri, S., 2008. A game-theoretic analysis of wireless access point selection by mobile users. Computer Communications, 31(10), pp.2049-2062.
Fahimullah, K. and Hassan, S., 2010, March. Game-theory based wireless access point selection scheme. In IEEE Silver Jubilee International Multitopic Symposium (SIMTS).
Khan, M.A., Toseef, U., Marx, S. and Goerg, C., 2010, May. Game-theory based user centric network selection with media independent handover services and flow management. In 2010 8th Annual Communication Networks and Services Research Conference, pp. 248-255. IEEE.
Khan, M.A., Toseef, U., Marx, S. and Goerg, C., 2010, April. Auction based interface selection with Media Independent Handover services and flow management. In 2010 European Wireless Conference (EW) (pp. 429-436). IEEE.
Pourkabirian, A., Fooladi, M.D.T., Zeinali, E. and Rahmani, A.M., 2018. Dynamic resource allocation for OFDMA femtocell networks: a game-theoretic approach. Telecommunication Systems, 69(1), pp.51-59.
Pourkabirian, A., Fooladi, M.D.T., Khosraghi, E.Z. and Rahmani, A.M., 2019. An Evolutionary Game-Theoretic Approach for Base Station Allocation in Wireless Femtocell Networks. Wireless Personal Communications, 107(1), pp.217-242.
Zhang, H., Jiang, C., Beaulieu, N.C., Chu, X., Wang, X. and Quek, T.Q., 2015. Resource allocation for cognitive small cell networks: A cooperative bargaining game theoretic approach. IEEE Transactions on Wireless Communications, 14(6), pp.3481-3493.
eng, Z., Song, L., Han, Z. and Zhao, X., 2013, April. Cell selection in two-tier femtocell networks with open/closed access using evolutionary game. In 2013 IEEE wireless communications and networking conference (WCNC) (pp. 860-865). IEEE.
Niyato, D. and Hossain, E., 2008. Dynamics of network selection in heterogeneous wireless networks: An evolutionary game approach. IEEE transactions on vehicular technology, 58(4).
Weibull, J.W., 1997. Evolutionary game theory. MIT press.
Specif. Group Radio Access Network - Physical Channel and Modulation (Release 8), 3GPP TS 36.211.
Seldin, Y., Szepesvári, C., Auer, P. and Abbasi-Yadkori, Y., 2012, December. Evaluation and Analysis of the Performance of the EXP3 Algorithm in Stochastic Environments. In EWRL (pp. 103-116).
