Energy harvesting empowered cognitive metro-cellular networks

Abstract

Abstract-Harvesting energy from natural (solar, wind, vibration etc.) and synthesized (microwave power transfer) sources is envisioned as a key enabler for realizing green wireless networks. Energy efficient scheduling is one of the prime objectives of cognitive radio platforms. To that end, in this article, we present a comprehensive analytical framework to characterize the performance of a cognitive metro-cellular network empowered by the solar energy harvesting. The proposed model considers both spatial and temporal dynamics of the energy field and the mobile user traffic. Channel uncertainties are also captured in terms of a large scale path-loss and a small-scale Rayleigh fading. A new metric called 'energy outage probability' which characterizes the self-sustainable operation of the base stations under energy harvesting is proposed and quantified. It is shown that the energy outage probability is strongly coupled with the path-loss exponent, required quality-of-service, base station and user density. Moreover, the energy outage probability varies both on a daily and yearly basis depending on the solar geoemtry. It is shown that even in winter time BS can run 10-15 hours without any purchase of energy from the power grid.

Multichannel-Sensing Scheduling and Transmission-Energy Optimizing in Cognitive Radio Networks with Energy Harvesting

“…In addition, harvesting power and green energy-powered CRNs have recently gained considerable attention [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ]. Specifically, the architecture, technical challenges, performance and applications of green energy-powered CRNs have been analyzed in [ 12 , 19 , 20 , 21 ] and the references therein.…”

“…However, green power is still envisioned as an important energy resource to liberate CRNs from energy constraints in the future. Meanwhile, state-of-the-art energy-efficient harvesting energy-powered CRNs have been investigated from various aspects, such as: solar energy harvesting-powered cognitive metro cellular network [ 16 ], cognitive radio transmitting-harvesting energy [ 16 , 17 ], relay, optimal energy allocation, transmission energy optimization [ 12 , 18 , 22 , 23 , 24 ] and packet transmission period optimization [ 25 ]. Obviously, the constraints in battery capacity and energy-harvested capacity should be considered as one of the major design criteria for future green-powered CRNS.…”