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Title: Antenna allocation and pricing in virtualized massive MIMO networks via Stackelberg game
Authors: Liu, Ye
Derakhshani, Mahsa
Parsaeefard, Saeedeh
Lambotharan, Sangarapillai
Wong, Kai-Kit
Keywords: Resource allocation
Massive MIMO
Stackelberg games
Convex approximation
Antenna allocation
Issue Date: 2018
Publisher: Institute of Electrical and Electronics Engineers
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.
Abstract: 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.
Description: 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/
Sponsor: 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.
Version: Published
DOI: 10.1109/TCOMM.2018.2846574
URI: https://dspace.lboro.ac.uk/2134/33564
Publisher Link: https://doi.org/10.1109/TCOMM.2018.2846574
ISSN: 0090-6778
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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