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SCIENCE CHINA Information Sciences, Volume 60, Issue 2: 022306(2017) https://doi.org/10.1007/s11432-015-0625-3

Competitive access in multi-RAT systems with regulated interference constraints

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  • ReceivedDec 22, 2015
  • AcceptedFeb 24, 2016
  • PublishedNov 9, 2016

Abstract

Deployment of multiple radio access technologies (RATs) at the same cell site enables the system to flexibly support different types of devices and services. Such multi-RAT systems call for an efficient utilization of the system resources as well as simplified management. In this paper, we take a user-centric approach and let each individual user equipment decide its own access strategy in a multi-RAT system with regulated interference constraints. The formulated problem is a generalized Nash equilibrium (GNE) problem. We show that there always exists a GNE but its uniqueness is not guaranteed. A closed form solution is provided to characterize a special class of the GNEs. We then propose a primal-dual algorithm with detailed convergence analysis for computing a GNE. The proposed algorithm may have practical implications in the design of multi-RAT systems.


Funded by

. The authors gratefully acknowledge Dr. Xingqin Lin(Ericsson Research)

National High Technology Research and Development Program of China(863)

National Science and Technology Major Project of China(2012ZX03001003-003)

"source" : null , "contract" : "2014AA01A704"

National Natural Science Foundation of China(61101092)

"source" : null , "contract" : "2014AA01A706"

Fundamental Research Funds for the Central Universities(ZYGX2015J014)

National Natural Science Foundation of China(61571003)


Acknowledgment

Acknowledgments

This work was supported by National Natural Science Foundation of China (Grant Nos. 61101092, 61571003), National Science and Technology Major Project of China (Grant No. 2012ZX03001003-003), National High Technology Research and Development Program of China (863) (Grant Nos. 2014AA01A704, 2014AA01A706), and Fundamental Research Funds for the Central Universities (Grant No. ZYGX2015J014). The authors gratefully acknowledge Dr. Xingqin Lin (Ericsson Research) for his help in identifying the problem and detailed technical discussions.


References

[1] Ericsson. 5G Radio Access: Research and Vision. White Paper. http://www.ericsson.com/res/docs/whitepapers/wp-5g.pdf. 2013. Google Scholar

[2] Andrews J G, Buzzi S, Choi W, et al. What will 5G be? IEEE J Sel Areas Commun, 2014, 32: 1065--1082. Google Scholar

[3] Wireless World Research Forum Working Group C. Multi-RAT network architecture. White Paper. http://www.wwrf. ch/files/wwrf/content/files/publications/outlook/Outlook9.pdf. 2013. Google Scholar

[4] Hasib A, Fapojuwo A. Analysis of common radio resource management scheme for end-to-end QoS support in multiservice heterogeneous wireless networks. IEEE Trans Veh Tech, 2008, 57: 2426-2439 CrossRef Google Scholar

[5] Ong E H, Khan J Y. On optimal network selection in a dynamic multi-RAT environment. IEEE Commun Lett, 2010, 14: 217-219 CrossRef Google Scholar

[6] Mu{\ n}oz P, Laselva D, Barco R, et al. Dynamic traffic steering based on fuzzy Q-learning approach in a multi-RAT multi-layer wireless network. Comput Netw, 2014, 71: 100-116 CrossRef Google Scholar

[7] Pollakis E, Cavalcante R L G, Stanczak S. Enhancing energy efficient network operation in multi-RAT cellular environments through sparse optimization. In: Proceedings of IEEE Workshop on Signal Processing Advances in Wireless Communications, Darmstadt, 2013. 260--264. Google Scholar

[8] Chiasserini C F, Gribaudo M, Manini D. Traffic offloading/onloading in multi-RAT cellular networks. In: Proceedings of IEEE IFIP Wireless Days, Valencia, 2013. 1--7. Google Scholar

[9] Choi Y, Kim H, Han S W, et al. Joint resource allocation for parallel multi-radio access in heterogeneous wireless networks. IEEE Trans Wirel Commun, 2010, 9: 3324-3329 CrossRef Google Scholar

[10] Lim G, Xiong C, Cimini L, et al. Energy-efficient resource allocation for OFDMA-based multi-RAT networks. IEEE Trans Wirel Commun, 2014, 13: 2696-2705 CrossRef Google Scholar

[11] Alsohaily A, Sousa E S. Unified radio access network operation for multi-radio access technology cellular systems. In: Proceedings of IEEE International Conference on Telecommunications, Lisbon, 2014. 32--36. Google Scholar

[12] Ma X, Sheng M, Zhang Y. Flow splitting for multi-RAT heterogeneous networks. In: Proceedings of IEEE Vehicular Technology Conference, Quebec City, 2012. 1--5. Google Scholar

[13] Yeh S P, Panah A Y, Himayat N, et al. QoS aware scheduling and cross-radio coordination in multi-radio heterogeneous networks. In: Proceedings of IEEE Vehicular Technology Conference, Las Vegas, 2013. 1--6. Google Scholar

[14] Facchinei F, Kanzow C. Generalized Nash equilibrium problems. 4OR-Q J Oper Res, 2007, 5: 173-210 CrossRef Google Scholar

[15] Chen M, Ponec M, Sengupta S, et al. Utility maximization in peer-to-peer systems. SIGMETRICS Perform Eval Rev, 2008, 36: 169-180 CrossRef Google Scholar

[16] Lin X, Lok T M. Distributed power control for one-to-many transmissions in Gaussian interference channels. IEEE Trans Commun, 2012, 60: 2363-2375 CrossRef Google Scholar

[17] Monderer D, Shapley L S. Potential games. Games Econ Behav, 1996, 14: 124-143 CrossRef Google Scholar

[18] Boyd S, Lieven V. Convex Optimization. New York: Cambridge University Press, 2004. 241--249. Google Scholar

[19] Khalil H, Grizzle J. Nonlinear Systems. New Jersey: Prentice Hall, 2002. 237--242. Google Scholar

[20] Lin X, Andrews J G, Ghosh A, et al. An overview of 3GPP device-to-device proximity services. IEEE Commun Mag, 2014, 52: 40-48 Google Scholar

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