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Antenna allocation and pricing in virtualized massive MIMO networks via Stackelberg game

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journal contribution
posted on 27.06.2018, 10:21 by Ye Liu, Mahsa Derakhshani, Saeedeh Parsaeefard, Sangarapillai Lambotharan, Kai-Kit Wong
We study a resource allocation problem for the uplink of a virtualized massive multiple-input multiple-output (MIMO) system, where the antennas at the base station are priced and virtualized among the service providers (SPs). The mobile network operator (MNO) who owns the infrastructure decides the price per antenna, and a Stackelberg game is formulated for the net profit maximization of the MNO, while minimum rate requirements of SPs are satisfied. To solve the bi-level optimization problem of the MNO, we first derive the closed-form best responses of the SPs with respect to the pricing strategies of the MNO, such that the problem of the MNO can be reduced to a single-level optimization. Then, via transformations and approximations, we cast the MNO’s problem with integer constraints into a signomial geometric program (SGP), and we propose an iterative algorithm based on the successive convex approximation (SCA) to solve the SGP. Simulation results show that the proposed algorithm has performance close to the global optimum. Moreover, the interactions between the MNO and SPs in different scenarios are explored via simulations.

Funding

This work has been supported by the Engineering and Physical Science Research Council of the UK, EPSRC, under the grants EP/M015475 and EP/M016005.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Transactions on Communications

Citation

LIU, Y. ...et al., 2018. Antenna allocation and pricing in virtualized massive MIMO networks via Stackelberg game. IEEE Transactions on Communications, 66(11), pp. 5220 - 5234.

Publisher

Institute of Electrical and Electronics Engineers

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/

Acceptance date

31/05/2018

Publication date

2018-06-12

Notes

This is an Open Access Article. It is published by IEEE under the Creative Commons Attribution 3.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/3.0/

ISSN

0090-6778

Language

en

Licence

Exports