25,811 research outputs found
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
Estimation Diversity and Energy Efficiency in Distributed Sensing
Distributed estimation based on measurements from multiple wireless sensors
is investigated. It is assumed that a group of sensors observe the same
quantity in independent additive observation noises with possibly different
variances. The observations are transmitted using amplify-and-forward (analog)
transmissions over non-ideal fading wireless channels from the sensors to a
fusion center, where they are combined to generate an estimate of the observed
quantity. Assuming that the Best Linear Unbiased Estimator (BLUE) is used by
the fusion center, the equal-power transmission strategy is first discussed,
where the system performance is analyzed by introducing the concept of
estimation outage and estimation diversity, and it is shown that there is an
achievable diversity gain on the order of the number of sensors. The optimal
power allocation strategies are then considered for two cases: minimum
distortion under power constraints; and minimum power under distortion
constraints. In the first case, it is shown that by turning off bad sensors,
i.e., sensors with bad channels and bad observation quality, adaptive power
gain can be achieved without sacrificing diversity gain. Here, the adaptive
power gain is similar to the array gain achieved in Multiple-Input
Single-Output (MISO) multi-antenna systems when channel conditions are known to
the transmitter. In the second case, the sum power is minimized under
zero-outage estimation distortion constraint, and some related energy
efficiency issues in sensor networks are discussed.Comment: To appear at IEEE Transactions on Signal Processin
Automatic goal allocation for a planetary rover with DSmT
In this chapter, we propose an approach for assigning aninterest level to the goals of a planetary rover. Assigning an interest level to goals, allows the rover to autonomously transform and reallocate the goals. The interest level is defined by data-fusing payload and navigation information. The fusion yields an 'interest map',that quantifies the level of interest of each area around the rover. In this way the planner can choose the most interesting scientific objectives to be analysed, with limited human intervention, and reallocates its goals autonomously. The Dezert-Smarandache Theory of Plausible and Paradoxical Reasoning was used for information fusion: this theory allows dealing with vague and conflicting data. In particular, it allows us to directly model the behaviour of the scientists that have to evaluate the relevance of a particular set of goals. This chaptershows an application of the proposed approach to the generation of a reliable interest map
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
Uncertainty in Ontologies: Dempster-Shafer Theory for Data Fusion Applications
Nowadays ontologies present a growing interest in Data Fusion applications.
As a matter of fact, the ontologies are seen as a semantic tool for describing
and reasoning about sensor data, objects, relations and general domain
theories. In addition, uncertainty is perhaps one of the most important
characteristics of the data and information handled by Data Fusion. However,
the fundamental nature of ontologies implies that ontologies describe only
asserted and veracious facts of the world. Different probabilistic, fuzzy and
evidential approaches already exist to fill this gap; this paper recaps the
most popular tools. However none of the tools meets exactly our purposes.
Therefore, we constructed a Dempster-Shafer ontology that can be imported into
any specific domain ontology and that enables us to instantiate it in an
uncertain manner. We also developed a Java application that enables reasoning
about these uncertain ontological instances.Comment: Workshop on Theory of Belief Functions, Brest: France (2010
Reconfiguration of Distributed Information Fusion System ? A case study
Information Fusion Systems are now widely used in different fusion contexts,
like scientific processing, sensor networks, video and image processing. One of
the current trends in this area is to cope with distributed systems. In this
context, we have defined and implemented a Dynamic Distributed Information
Fusion System runtime model. It allows us to cope with dynamic execution
supports while trying to maintain the functionalities of a given Dynamic
Distributed Information Fusion System. The paper presents our system, the
reconfiguration problems we are faced with and our solutions.Comment: 6 pages - Preprint versio
A schema for generic process tomography sensors
A schema is introduced that aims to facilitate the widespread exploitation of the science of process tomography (PT) that promises a unique multidimensional sensing opportunity. Although PT has been developed to an advanced state, applications have been laboratory or pilot-plant based, configured on an end-to-end basis, and limited typically to the formation of images that attempt to represent process contents. The schema facilitates the fusion of multidimensional internal process state data in terms of a model that yields directly usable process information, either for design model confirmation or for effective plant monitoring or control, here termed a reality visualization model (RVM). A generic view leads to a taxonomy of process types and their respective RVM. An illustrative example is included and a review of typical sensor system components is given
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