University of Oulu

T. Sanguanpuak, S. Guruacharya, N. Rajatheva, M. Bennis and M. Latva-Aho, "Multi-Operator Spectrum Sharing for Small Cell Networks: A Matching Game Perspective," in IEEE Transactions on Wireless Communications, vol. 16, no. 6, pp. 3761-3774, June 2017. doi: 10.1109/TWC.2017.2688392

Multi-operator spectrum sharing for small cell network : a matching game perspective

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Author: Sanguanpuak, Tachporn1; Guruacharya, Sudarshan2; Rajatheva, Nandana1;
Organizations: 1Centre for Wireless Communications, University of Oulu, 90014 Oulu, Finland
2Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.3 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2018080633405
Language: English
Published: Institute of Electrical and Electronics Engineers, 2017
Publish Date: 2018-08-06
Description:

Abstract

One of the many problems faced by current cellular network technology is the underutilization of the dedicated licensed spectrum of network operators. An emerging paradigm to solve this issue is to allow multiple operators to share some parts of each other's spectrum. Previous works on spectrum sharing have failed to integrate the theoretical insights provided by recent developments in stochastic geometrical approaches to cellular network analysis with the objectives of network resource allocation problems. In this paper, we study the non-orthogonal spectrum assignment with the goal of maximizing the social welfare of the network, defined as the expected weighted sum rate of the operators. We adopt the many-to-one stable matching game framework to tackle this problem. Moreover, using the stochastic geometrical approach, we show that its solution can be both stable as well as socially optimal. To obtain the maxima of social welfare, the computation of the game theoretical solution using the generic Markov Chain Monte Carlo method is proposed. We also investigate the role of power allocation schemes using Q-learning, and we numerically show that the effect of resource allocation scheme is much more significant than the effect of power allocation for the social welfare of the system.

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Series: IEEE transactions on wireless communications
ISSN: 1536-1276
ISSN-E: 1558-2248
ISSN-L: 1536-1276
Volume: 16
Issue: 6
Pages: 3761 - 3774
DOI: 10.1109/TWC.2017.2688392
OADOI: https://oadoi.org/10.1109/TWC.2017.2688392
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
5G
Funding: This work was supported in part by the Finnish Funding Agency for Technology and Innovation (TEKES), in part by Nokia Networks, in part by Anite Telecoms, in part by Huawei Technologies, in part by Broadcom Communications Finland, in part by Elektrobit Wireless Communications, in part by the Infotech Oulu Graduate School, and in part by the Natural Sciences and Engineering Research Council of Canada.
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