  Designing mobiles to harvest ambient energy such as kinetic activities or
electromagnetic radiation will enable wireless networks to be self sustaining
besides alleviating global warming. In this paper, the spatial throughput of a
mobile ad hoc network powered by energy harvesting is analyzed using a
stochastic-geometry model. In this model, transmitters are distributed as a
Poisson point process and energy arrives at each transmitter randomly with a
uniform average rate called the energy arrival rate; upon harvesting sufficient
energy, each transmitter transmits with fixed power to an intended receiver
under an outage-probability constraint for a target
signal-to-interference-and-noise ratio. It is assumed that transmitters store
energy in batteries with infinite capacity. By applying the random-walk theory,
the probability that a transmitter transmits, called the transmission
probability, is proved to be equal to one if the energy-arrival rate exceeds
transmission power or otherwise is equal to their ratio. This result and tools
from stochastic geometry are applied to maximize the network throughput for a
given energy-arrival rate by optimizing transmission power. The maximum network
throughput is shown to be proportional to the optimal transmission probability,
which is equal to one if the transmitter density is below a derived function of
the energy-arrival rate or otherwise is smaller than one and solves a given
polynomial equation. Last, the limits of the maximum network throughput are
obtained for the extreme cases of high energy-arrival rates and dense networks.
