Dual-Battery Enabled Profit Driven User Association in Green Heterogeneous Cellular Networks

Xilong Liu, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

With awareness of the potential harmful effects to the environment and climate change, on-grid brown energy consumption of information and communications technology (ICT) has drawn much attention. Cellular base stations (BSs) are among the major energy guzzlers in ICT, and their contributions to the global carbon emissions increase sustainedly. It is essential to leverage green energy to power BSs to reduce their on-grid brown energy consumption. However, in order to furthest save on-grid brown energy and decrease the on-grid brown energy electricity expenses, most existing green energy related works only pursue to maximize the green energy utilization, while compromising the services received by the mobile users. In reality, dissatisfaction of services may eventually lead to loss of market shares and profits of the network providers. In this paper, we propose a dual-battery enabled profit driven user association scheme by jointly considering the traffic delivery latency and green energy utilization to maximize the profits for the network providers in heterogeneous cellular networks. Since this profit driven user association optimization problem is NP-hard, we further propose some heuristics to solve the problem with low computational complexity. Finally, the performance of the proposed algorithm has been validated through extensive simulations.

Original languageEnglish (US)
Article number8456544
Pages (from-to)1002-1011
Number of pages10
JournalIEEE Transactions on Green Communications and Networking
Volume2
Issue number4
DOIs
StatePublished - Dec 2018

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Computer Networks and Communications

Keywords

  • Green heterogeneous cellular networks
  • dual-battery
  • green energy harvesting
  • profit maximization
  • traffic delivery latency
  • user association

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