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

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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 realtime energy demand. More specifically, this paper formulates two sparse optimization problems and applies reweighted ℓ1- norm approximation for ℓ0-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.
Original languageEnglish
Article number7565627
Pages (from-to)2022 - 2031
Number of pages10
JournalIEEE Transactions on Smart Grid
Issue number4
Early online date13 Sept 2016
Publication statusPublished - Jul 2017


  • C-RAN
  • fronthaul link capacity constraints
  • real-time energy trading
  • sparse beamforming


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