On Green-Energy-Powered Cognitive Radio Networks

• Published in: IEEE Communications surveys and tutorials Vol. 17; no. 2; pp. 827 - 842
• Main Authors: Xueqing Huang, Tao Han, Ansari, Nirwan
• Format: Journal Article
• Language: English
• Published: IEEE 01-01-2015
• Subjects: Cognitive radio; Cognitive radio (CR); energy efficiency; energy harvesting; Green products; Interference; Power demand; Resource management; Sensors; spectrum efficiency; Wireless networks; spectrum efficiency; energy harvesting; Cognitive radio (CR); energy efficiency
• ISSN: 1553-877X
• DOI: 10.1109/COMST.2014.2387697

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.