T. Sanguanpuak, S. Guruacharya, E. Hossain, N. Rajatheva and M. Latva-aho, "Infrastructure Sharing for Mobile Network Operators: Analysis of Trade-Offs and Market," in IEEE Transactions on Mobile Computing, vol. 17, no. 12, pp. 2804-2817, 1 Dec. 2018. doi: 10.1109/TMC.2018.2822291
Infrastructure sharing for mobile network operators : analysis of trade-offs and market
|Author:||Sanguanpuak, Tachporn1; Guruacharya, Sudarshan2; Hossain, Ekram2;|
1Centre for Wireless Communications (CWC), Department of Communications Engineering, University of Oulu, Oulu 90014, Finland
2Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
|Online Access:||PDF Full Text (PDF, 2.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2019052917652
IEEE Computer Society,
|Publish Date:|| 2019-05-29
The conflicting problems of growing mobile service demand and underutilization of dedicated spectrum has given rise to a paradigm where mobile network operators (MNOs) share their infrastructure among themselves in order to lower their operational costs, while at the same time increase the usage of their existing network resources. We model and analyze such an infrastructure sharing system considering a single buyer MNO and multiple seller MNOs. Assuming that the locations of the BSs can be modeled as a homogeneous Poisson point process, we find the downlink signal-to-interference-plus-noise ratio (SINR) coverage probability for a user served by the buyer MNO in an infrastructure sharing environment. We analyze the trade-off between increasing the transmit power of a base station (BS) and the intensity of BSs owned by the buyer MNO required to achieve a given quality-of-service (QoS) in terms of the SINR coverage probability. Also, for a seller MNO, we analyze the power consumption of the network per unit area (i.e., areal power consumption) which is shown to be a piecewise continuous function of BS intensity, composed of a linear and a convex function. Accordingly, the BS intensity of the seller MNO can be optimized to minimize the areal power consumption while achieving a minimum QoS for the buyer MNO. We then use these results to formulate a single-buyer multiple-seller BS infrastructure market. The buyer MNO is concerned with finding which seller MNO to purchase from and what fraction of BSs to purchase. On the sellers’ side, the problem of pricing and determining the fraction of infrastructure to be sold is formulated as a Cournot oligopoly market. We prove that the iterative update of each seller’s best response always converges to the Nash Equilibrium.
IEEE transactions on mobile computing
|Pages:||2804 - 2817|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was supported in part by a Discovery Grant (RGPIN-2014-03840) from the Natural Sciences and Engineering Research Council of Canada (NSERC).
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.