  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.
