Energy harvesting empowered cognitive metro-cellular networks

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 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 large scale path-loss and 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 daily and yearly basis depending on the solar geometry. It is shown that even in winter time BSs can run for 10-15 hours without any purchase of energy from the power grid.