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Sparse Beamforming for Real-Time Resource Management and Energy Trading in Green C-RAN

Wan Ariffin, Wan Nur Suryani Firuz and Zhang, Xinruo and Nakhai, Mohammad Reza (2017) 'Sparse Beamforming for Real-Time Resource Management and Energy Trading in Green C-RAN.' IEEE Transactions on Smart Grid, 8 (4). pp. 2022-2031. ISSN 1949-3053

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This paper considers cloud radio access network with simultaneous wireless information and power transfer and finite capacity fronthaul, where the remote radio heads are equipped with renewable energy resources and can trade energy with the grid. Due to uneven distribution of mobile radio traffic and inherent intermittent nature of renewable energy resources, the remote radio heads may need real-time energy provisioning to meet the users' demands. Given the amount of available energy resources at remote radio heads, this paper introduces two provisioning strategies to strike an optimum balance among the total power consumption in the fronthaul, through adjusting the degree of partial cooperation among the remote radio heads, the total transmit power and the maximum or the overall real-time energy demand. More specifically, this paper formulates two sparse optimization problems and applies reweighted ℓ 1 -norm approximation for ℓ 0 -norm and semidefinite relaxation to develop two iterative algorithms for the proposed strategies. Simulation results confirm that both of the proposed strategies outperform two other recently proposed schemes in terms of improving energy efficiency and reducing overall energy cost of the network.

Item Type: Article
Uncontrolled Keywords: C-RAN; real-time energy trading; sparse beamforming; SWIPT; fronthaul link capacity constraints
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 20 May 2020 16:31
Last Modified: 15 Jan 2022 01:31

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