4,638 research outputs found
On the Effects of Battery Imperfections in an Energy Harvesting Device
Energy Harvesting allows the devices in a Wireless Sensor Network to recharge
their batteries through environmental energy sources. While in the literature
the main focus is on devices with ideal batteries, in reality several
inefficiencies have to be considered to correctly design the operating regimes
of an Energy Harvesting Device (EHD). In this work we describe how the
throughput optimization problem changes under \emph{real battery} constraints
in an EHD. In particular, we consider imperfect knowledge of the state of
charge of the battery and storage inefficiencies, \emph{i.e.}, part of the
harvested energy is wasted in the battery recharging process. We formulate the
problem as a Markov Decision Process, basing our model on some realistic
observations about transmission, consumption and harvesting power. We find the
performance upper bound with a real battery and numerically discuss the novelty
introduced by the real battery effects. We show that using the \emph{old}
policies obtained without considering the real battery effects is strongly
sub-optimal and may even result in zero throughput.Comment: In Proc. IEEE International Conference on Computing, Networking and
Communications, pp. 942-948, Feb. 201
Energy Harvesting Communication System with SOC-Dependent Energy Storage Losses
The popularity of Energy Harvesting Devices (EHDs) has grown in the past few
years, thanks to their capability of prolonging the network lifetime. In
reality, EHDs are affected by several inefficiencies, e.g., energy leakage,
battery degradation or storage losses. In this work we consider an energy
harvesting transmitter with storage inefficiencies. In particular, we assume
that when new energy has to be stored in the battery, part of this is wasted
and the losses depend upon the current state of charge of the device. This is a
practical realistic assumption, e.g., for a capacitor, that changes the
structure of the optimal transmission policy. We analyze the throughput
maximization problem with a dynamic programming approach and prove that, given
the battery status and the channel gain, the optimal transmission policy is
deterministic. We derive numerical results for the energy losses in a capacitor
and show the presence of a \emph{loop effect} that degrades the system
performance if the optimal policy is not considered.Comment: In Proc. IEEE Twelfth Int. Symposium on Wireless Communication
Systems (ISWCS), pp. 406-410, Aug. 201
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
Optimal Compression and Transmission Rate Control for Node-Lifetime Maximization
We consider a system that is composed of an energy constrained sensor node
and a sink node, and devise optimal data compression and transmission policies
with an objective to prolong the lifetime of the sensor node. While applying
compression before transmission reduces the energy consumption of transmitting
the sensed data, blindly applying too much compression may even exceed the cost
of transmitting raw data, thereby losing its purpose. Hence, it is important to
investigate the trade-off between data compression and transmission energy
costs. In this paper, we study the joint optimal compression-transmission
design in three scenarios which differ in terms of the available channel
information at the sensor node, and cover a wide range of practical situations.
We formulate and solve joint optimization problems aiming to maximize the
lifetime of the sensor node whilst satisfying specific delay and bit error rate
(BER) constraints. Our results show that a jointly optimized
compression-transmission policy achieves significantly longer lifetime (90% to
2000%) as compared to optimizing transmission only without compression.
Importantly, this performance advantage is most profound when the delay
constraint is stringent, which demonstrates its suitability for low latency
communication in future wireless networks.Comment: accepted for publication in IEEE Transactions on Wireless
Communicaiton
Towards Self-Control of Service Rate for Battery Management in Energy Harvesting Devices
We consider the operation of an energy harvesting wireless device (sensor node) powered by a rechargeable battery, taking non-idealities into account. In particular, we consider sudden decrease and increase of the battery level (leakage and charge recovery consequently) due to the inner diffusion processes in the battery. These processes are affecting the stability of the device operation. In particular, leakage accelerates the depletion of the battery, which results in inactive periods of the device and, thus, potential data loss. In this paper, we propose a simplified self-control management of a battery expressed by restrictions, which could be used for an efficient operational strategy of the device. To achieve this, we rely on the double-queue model which includes the imperfections of the battery operation and bi-dimensional battery value. This includes both apparent, i.e., available at the electrodes and true energy levels of a battery. These levels can be significantly different because of deep discharge events and can equalize thanks to charge recovery effect. We performed some simulation and observed that we can diminish the models variable number to predict possible unwanted events such as apparent discharge events (when the areas near electrodes are depleted while other areas of the battery still contain some energy) and data losses. This observation helps to achieve sufficiently effective self-control management by knowing and managing just few parameters, and therefore offers valuable directions for the development of autonomic and self-sustainable operation
Optimal multi-user transmission strategies for Energy Harvesting devices - Strategie ottime di trasmissione multi-utente per dispositivi Energy Harvesting
In this thesis a pair of energy harvesting devices (EHDs) is considered, whose state at any given time is determined by the energy level and an importance value, associated to the transmission of a data packet to the receiver at that particular time. For each device, the objective is to optimize the transmission strategy of the two nodes over a shared wireless channel, with the goal of maximizing the long-term average importance of the transmitted dat
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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