899 research outputs found
Optimal Save-Then-Transmit Protocol for Energy Harvesting Wireless Transmitters
In this paper, the design of a wireless communication device relying
exclusively on energy harvesting is considered. Due to the inability of
rechargeable energy sources to charge and discharge at the same time, a
constraint we term the energy half-duplex constraint, two rechargeable energy
storage devices (ESDs) are assumed so that at any given time, there is always
one ESD being recharged. The energy harvesting rate is assumed to be a random
variable that is constant over the time interval of interest. A
save-then-transmit (ST) protocol is introduced, in which a fraction of time
{\rho} (dubbed the save-ratio) is devoted exclusively to energy harvesting,
with the remaining fraction 1 - {\rho} used for data transmission. The ratio of
the energy obtainable from an ESD to the energy harvested is termed the energy
storage efficiency, {\eta}. We address the practical case of the secondary ESD
being a battery with {\eta} < 1, and the main ESD being a super-capacitor with
{\eta} = 1. The optimal save-ratio that minimizes outage probability is
derived, from which some useful design guidelines are drawn. In addition, we
compare the outage performance of random power supply to that of constant power
supply over the Rayleigh fading channel. The diversity order with random power
is shown to be the same as that of constant power, but the performance gap can
be large. Furthermore, we extend the proposed ST protocol to wireless networks
with multiple transmitters. It is shown that the system-level outage
performance is critically dependent on the relationship between the number of
transmitters and the optimal save-ratio for single-channel outage minimization.
Numerical results are provided to validate our proposed study.Comment: This is the longer version of a paper to appear in IEEE Transactions
on Wireless Communication
Energy Harvesting Wireless Communications: A Review of Recent Advances
This article summarizes recent contributions in the broad area of energy
harvesting wireless communications. In particular, we provide the current state
of the art for wireless networks composed of energy harvesting nodes, starting
from the information-theoretic performance limits to transmission scheduling
policies and resource allocation, medium access and networking issues. The
emerging related area of energy transfer for self-sustaining energy harvesting
wireless networks is considered in detail covering both energy cooperation
aspects and simultaneous energy and information transfer. Various potential
models with energy harvesting nodes at different network scales are reviewed as
well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications
(Special Issue: Wireless Communications Powered by Energy Harvesting and
Wireless Energy Transfer
Optimization of the overall success probability of the energy harvesting cognitive wireless sensor networks
Wireless energy harvesting can improve the performance of cognitive wireless sensor networks (WSNs). This paper considers radio frequency (RF) energy harvesting from transmissions in the primary spectrum for cognitive WSNs. The overall success probability of the energy harvesting cognitive WSN depends on the transmission success probability and energy success probability. Using the tools from stochastic geometry, we show that the overall success probability can be optimized with respect to: 1) transmit power of the sensors; 2) transmit power of the primary transmitters; and 3) spatial density of the primary transmitters. In this context, an optimization algorithm is proposed to maximize the overall success probability of the WSNs. Simulation results show that the overall success probability and the throughput of the WSN can be significantly improved by optimizing the aforementioned three parameters. As RF energy harvesting can also be performed indoors, hence, our solution can be directly applied to the cognitive WSNs that are installed in smart buildings
Joint Transmission and Energy Transfer Policies for Energy Harvesting Devices with Finite Batteries
One of the main concerns in traditional Wireless Sensor Networks (WSNs) is
energy efficiency. In this work, we analyze two techniques that can extend
network lifetime. The first is Ambient \emph{Energy Harvesting} (EH), i.e., the
capability of the devices to gather energy from the environment, whereas the
second is Wireless \emph{Energy Transfer} (ET), that can be used to exchange
energy among devices. We study the combination of these techniques, showing
that they can be used jointly to improve the system performance. We consider a
transmitter-receiver pair, showing how the ET improvement depends upon the
statistics of the energy arrivals and the energy consumption of the devices.
With the aim of maximizing a reward function, e.g., the average transmission
rate, we find performance upper bounds with and without ET, define both online
and offline optimization problems, and present results based on realistic
energy arrivals in indoor and outdoor environments. We show that ET can
significantly improve the system performance even when a sizable fraction of
the transmitted energy is wasted and that, in some scenarios, the online
approach can obtain close to optimal performance.Comment: 16 pages, 12 figure
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