On green-energy-powered cognitive radio networks

Xueqing Huang, Tao Han, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review

159 Scopus citations

Abstract

A green-energy-powered cognitive radio (CR) network is capable of liberating the wireless access networks from spectral and energy constraints. The limitation of the spectrum is alleviated by exploiting cognitive networking in which wireless nodes sense and utilize the spare spectrum for data communications, whereas dependence on the traditional unsustainable energy is assuaged by adopting energy harvesting through which green energy can be harnessed to power wireless networks. Green-energy-powered CR increases the network availability and thus extends emerging network applications. Designing green CR networks is challenging. It requires not only the optimization of dynamic spectrum access but also the optimal utilization of green energy. This paper surveys the energy-efficient CR techniques and the optimization of green-energy-powered wireless networks. Existing works on energy-aware spectrum sensing, management, and sharing are investigated in detail. The state of the art of the energy-efficient CR-based wireless access network is discussed in various aspects, such as relay and cooperative radio and small cells. Envisioning green energy as an important energy resource in the future, network performance highly depends on the dynamics of the available spectrum and green energy. As compared with the traditional energy source, the arrival rate of green energy, which highly depends on the environment of the energy harvesters, is rather random and intermittent. To optimize and adapt the usage of green energy according to the opportunistic spectrum availability, we discuss research challenges in designing CR networks that are powered by energy harvesters.

Original languageEnglish (US)
Article number7001217
Pages (from-to)827-842
Number of pages16
JournalIEEE Communications Surveys and Tutorials
Volume17
Issue number2
DOIs
StatePublished - Apr 1 2015

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Keywords

  • Cognitive radio (CR)
  • energy efficiency
  • energy harvesting
  • spectrum efficiency

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