15,700 research outputs found
Wireless Power Charging Control in Multiuser Broadband Networks
Recent advances in wireless power transfer (WPT) technology provide a
cost-effective solution to charge wireless devices remotely without disruption
to the use. In this paper, we propose an efficient wireless charging control
method for exploiting the frequency diversity in multiuser broadband wireless
networks, to reduce energy outage and keep the system operating in an efficient
and sustainable state. In particular, we first analyze the impact of charging
control method to the operating lifetime of a WPT-enabled broadband system.
Based on the analysis, we then propose a multi-criteria charging control policy
that optimizes the transmit power allocation over frequency by jointly
considering the channel state information (CSI) and the battery state
information (BSI) of wireless devices. For practical implementation, the
proposed scheme is realized by a novel limited CSI estimation mechanism
embedded with partial BSI, which significantly reduces the energy cost of CSI
and BSI feedback. Simulation results show that the proposed method could
significantly increase the network lifetime under stringent transmit power
constraint. Reciprocally, it also consumes lower transmit power to achieve
near-perpetual network operation than other single-criterion based charging
control methods.Comment: This paper had been accepted by IEEE ICC 2015, Workshop on Green
Communications and Networks with Energy Harvesting, Smart Grids, and
Renewable Energie
Photovoltaic sample-and-hold circuit enabling MPPT indoors for low-power systems
Photovoltaic (PV) energy harvesting is commonly used to power autonomous devices, and maximum power point tracking (MPPT) is often used to optimize its efficiency. This paper describes an ultra low-power MPPT circuit with a novel sample-and-hold and cold-start arrangement, enabling MPPT across the range of light intensities found indoors, which has not been reported before. The circuit has been validated in practice and found to cold-start and operate from 100 lux (typical of dim indoor lighting) up to 5000 lux with a 55cm2 amorphous silicon PV module. It is more efficient than non-MPPT circuits, which are the state-of-the-art for indoor PV systems. The proposed circuit maximizes the active time of the PV module by carrying out samples only once per minute. The MPPT control arrangement draws a quiescent current draw of only 8uA, and does not require an additional light sensor as has been required by previously-reported low-power MPPT circuits
SolarStat: Modeling Photovoltaic Sources through Stochastic Markov Processes
In this paper, we present a methodology and a tool to derive simple but yet
accurate stochastic Markov processes for the description of the energy
scavenged by outdoor solar sources. In particular, we target photovoltaic
panels with small form factors, as those exploited by embedded communication
devices such as wireless sensor nodes or, concerning modern cellular system
technology, by small-cells. Our models are especially useful for the
theoretical investigation and the simulation of energetically self-sufficient
communication systems including these devices. The Markov models that we derive
in this paper are obtained from extensive solar radiation databases, that are
widely available online. Basically, from hourly radiance patterns, we derive
the corresponding amount of energy (current and voltage) that is accumulated
over time, and we finally use it to represent the scavenged energy in terms of
its relevant statistics. Toward this end, two clustering approaches for the raw
radiance data are described and the resulting Markov models are compared
against the empirical distributions. Our results indicate that Markov models
with just two states provide a rough characterization of the real data traces.
While these could be sufficiently accurate for certain applications, slightly
increasing the number of states to, e.g., eight, allows the representation of
the real energy inflow process with an excellent level of accuracy in terms of
first and second order statistics. Our tool has been developed using Matlab(TM)
and is available under the GPL license at[1].Comment: Submitted to IEEE EnergyCon 201
Byzantine Attack and Defense in Cognitive Radio Networks: A Survey
The Byzantine attack in cooperative spectrum sensing (CSS), also known as the
spectrum sensing data falsification (SSDF) attack in the literature, is one of
the key adversaries to the success of cognitive radio networks (CRNs). In the
past couple of years, the research on the Byzantine attack and defense
strategies has gained worldwide increasing attention. In this paper, we provide
a comprehensive survey and tutorial on the recent advances in the Byzantine
attack and defense for CSS in CRNs. Specifically, we first briefly present the
preliminaries of CSS for general readers, including signal detection
techniques, hypothesis testing, and data fusion. Second, we analyze the spear
and shield relation between Byzantine attack and defense from three aspects:
the vulnerability of CSS to attack, the obstacles in CSS to defense, and the
games between attack and defense. Then, we propose a taxonomy of the existing
Byzantine attack behaviors and elaborate on the corresponding attack
parameters, which determine where, who, how, and when to launch attacks. Next,
from the perspectives of homogeneous or heterogeneous scenarios, we classify
the existing defense algorithms, and provide an in-depth tutorial on the
state-of-the-art Byzantine defense schemes, commonly known as robust or secure
CSS in the literature. Furthermore, we highlight the unsolved research
challenges and depict the future research directions.Comment: Accepted by IEEE Communications Surveys and Tutoiral
An adaptive envelope analysis in a wireless sensor network for bearing fault diagnosis using fast kurtogram algorithm
This paper proposes a scheme to improve the performance of applying envelope analysis in a wireless sensor network for bearing fault diagnosis. The fast kurtogram is realized on the host computer for determining an optimum band-pass filter for the envelope analysis that is implemented on the wireless sensor node to extract the low frequency fault information. Therefore, the vibration signal can be monitored over the bandwidth limited wireless sensor network with both intelligence and real-time performance. Test results have proved that the diagnostic information for different bearing faults can be successfully extracted using the optimum band-pass filter
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