Please use this identifier to cite or link to this item: https://doi.org/10.1109/TWC.2013.072613.130323
Title: Opportunistic wireless energy harvesting in cognitive radio networks
Authors: Lee, S.
Zhang, R. 
Huang, K.
Keywords: Cognitive radio
energy harvesting
opportunistic spectrum access
stochastic geometry
wireless power transfer
Issue Date: 2013
Source: Lee, S., Zhang, R., Huang, K. (2013). Opportunistic wireless energy harvesting in cognitive radio networks. IEEE Transactions on Wireless Communications 12 (9) : 4788-4799. ScholarBank@NUS Repository. https://doi.org/10.1109/TWC.2013.072613.130323
Abstract: Wireless networks can be self-sustaining by harvesting energy from ambient radio-frequency (RF) signals. Recently, researchers have made progress on designing efficient circuits and devices for RF energy harvesting suitable for low-power wireless applications. Motivated by this and building upon the classic cognitive radio (CR) network model, this paper proposes a novel method for wireless networks coexisting where low-power mobiles in a secondary network, called secondary transmitters (STs), harvest ambient RF energy from transmissions by nearby active transmitters in a primary network, called primary transmitters (PTs), while opportunistically accessing the spectrum licensed to the primary network. We consider a stochastic-geometry model in which PTs and STs are distributed as independent homogeneous Poisson point processes (HPPPs) and communicate with their intended receivers at fixed distances. Each PT is associated with a guard zone to protect its intended receiver from ST's interference, and at the same time delivers RF energy to STs located in its harvesting zone. Based on the proposed model, we analyze the transmission probability of STs and the resulting spatial throughput of the secondary network. The optimal transmission power and density of STs are derived for maximizing the secondary network throughput under the given outage-probability constraints in the two coexisting networks, which reveal key insights to the optimal network design. Finally, we show that our analytical result can be generally applied to a non-CR setup, where distributed wireless power chargers are deployed to power coexisting wireless transmitters in a sensor network. © 2013 IEEE.
Source Title: IEEE Transactions on Wireless Communications
URI: http://scholarbank.nus.edu.sg/handle/10635/71268
ISSN: 15361276
DOI: 10.1109/TWC.2013.072613.130323
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