462 research outputs found
Dynamic Modulation Yields One-Way Beam Splitting
This article demonstrates the realization of an extraordinary beam splitter
based on nonreciprocal and synchronized photonic transitions in obliquely
illuminated space-time-modulated (STM) slabs which impart the coherent temporal
frequency and spatial frequency shifts. As a consequence of such unusual
photonic transitions, a one-way beam splitting and amplification is exhibited
by the STM slab. Beam splitting is a vital operation for various optical and
photonic systems, ranging from quantum computation to fluorescence spectroscopy
and microscopy. Despite the beam splitting is conceptually a simple operation,
the performance characteristics of beam splitters significantly influence the
repeatability and accuracy of the entire optical system. As of today, there has
been no approach exhibiting a nonreciprocal beam splitting accompanied with
transmission gain and an arbitrary splitting angle. Here, we show that oblique
illumination of a periodic and semi-coherent dynamically-modulated slab results
in coherent photonic transitions between the incident light beam and its
counterpart space-time harmonic (STH). Such photonic transitions introduce a
unidirectional synchronization and momentum exchange between two STHs with same
temporal frequencies, but opposite spatial frequencies. Such a beam splitting
technique offers high isolation, transmission gain and zero beam tilting, and
is expected to drastically decrease the resource and isolation requirements in
optical and photonic systems. In addition to the analytical solution, we
provide a closed-form solution for the electromagnetic fields in STM
structures, and accordingly, investigate the properties of the wave isolation
and amplification in subluminal, superluminal and luminal ST modulations
Coexistence of RF-powered IoT and a Primary Wireless Network with Secrecy Guard Zones
This paper studies the secrecy performance of a wireless network (primary
network) overlaid with an ambient RF energy harvesting IoT network (secondary
network). The nodes in the secondary network are assumed to be solely powered
by ambient RF energy harvested from the transmissions of the primary network.
We assume that the secondary nodes can eavesdrop on the primary transmissions
due to which the primary network uses secrecy guard zones. The primary
transmitter goes silent if any secondary receiver is detected within its guard
zone. Using tools from stochastic geometry, we derive the probability of
successful connection of the primary network as well as the probability of
secure communication. Two conditions must be jointly satisfied in order to
ensure successful connection: (i) the SINR at the primary receiver is above a
predefined threshold, and (ii) the primary transmitter is not silent. In order
to ensure secure communication, the SINR value at each of the secondary nodes
should be less than a predefined threshold. Clearly, when more secondary nodes
are deployed, more primary transmitters will remain silent for a given guard
zone radius, thus impacting the amount of energy harvested by the secondary
network. Our results concretely show the existence of an optimal deployment
density for the secondary network that maximizes the density of nodes that are
able to harvest sufficient amount of energy. Furthermore, we show the
dependence of this optimal deployment density on the guard zone radius of the
primary network. In addition, we show that the optimal guard zone radius
selected by the primary network is a function of the deployment density of the
secondary network. This interesting coupling between the two networks is
studied using tools from game theory. Overall, this work is one of the few
concrete works that symbiotically merge tools from stochastic geometry and game
theory
Tight Lower Bounds on the Contact Distance Distribution in Poisson Hole Process
In this letter, we derive new lower bounds on the cumulative distribution
function (CDF) of the contact distance in the Poisson Hole Process (PHP) for
two cases: (i) reference point is selected uniformly at random from
independently of the PHP, and (ii) reference point is located at
the center of a hole selected uniformly at random from the PHP. While one can
derive upper bounds on the CDF of contact distance by simply ignoring the
effect of holes, deriving lower bounds is known to be relatively more
challenging. As a part of our proof, we introduce a tractable way of bounding
the effect of all the holes in a PHP, which can be used to study other
properties of a PHP as well.Comment: To appear in IEEE Wireless Communications Letter
Joint Uplink and Downlink Coverage Analysis of Cellular-based RF-powered IoT Network
Ambient radio frequency (RF) energy harvesting has emerged as a promising
solution for powering small devices and sensors in massive Internet of Things
(IoT) ecosystem due to its ubiquity and cost efficiency. In this paper, we
study joint uplink and downlink coverage of cellular-based ambient RF energy
harvesting IoT where the cellular network is assumed to be the only source of
RF energy. We consider a time division-based approach for power and information
transmission where each time-slot is partitioned into three sub-slots: (i)
charging sub-slot during which the cellular base stations (BSs) act as RF
chargers for the IoT devices, which then use the energy harvested in this
sub-slot for information transmission and/or reception during the remaining two
sub-slots, (ii) downlink sub-slot during which the IoT device receives
information from the associated BS, and (iii) uplink sub-slot during which the
IoT device transmits information to the associated BS. For this setup, we
characterize the joint coverage probability, which is the joint probability of
the events that the typical device harvests sufficient energy in the given time
slot and is under both uplink and downlink signal-to-interference-plus-noise
ratio (SINR) coverage with respect to its associated BS. This metric
significantly generalizes the prior art on energy harvesting communications,
which usually focused on downlink or uplink coverage separately. The key
technical challenge is in handling the correlation between the amount of energy
harvested in the charging sub-slot and the information signal quality (SINR) in
the downlink and uplink sub-slots. Dominant BS-based approach is developed to
derive tight approximation for this joint coverage probability. Several system
design insights including comparison with regularly powered IoT network and
throughput-optimal slot partitioning are also provided
Nearest Neighbor and Contact Distance Distribution for Binomial Point Process on Spherical Surfaces
This letter characterizes the statistics of the contact distance and the
nearest neighbor (NN) distance for binomial point processes (BPP)
spatially-distributed on spherical surfaces. We consider a setup of
concentric spheres, with each sphere has a radius and points
that are uniformly distributed on its surface. For that setup, we obtain the
cumulative distribution function (CDF) of the distance to the nearest point
from two types o observation points: (i) the observation point is not a part of
the point process and located on a concentric sphere with a radius
, which corresponds to the contact distance distribution, and
(ii) the observation point belongs to the point process, which corresponds to
the nearest-neighbor (NN) distance distribution
A fuzzy model and algorithm to handle subjectivity in life cycle costing based decision-making.
A life cycle costing (LCC) algorithm that can effectively deal with judgmental assessments of input parameters is proposed. This algorithm is based on the fuzzy set theory and interval mathematics. The development of the algorithm is motivated by the need to handle in a systematic and a more objective way the imprecision in these subjective assessments. Three major issues were considered in the development of the algorithm. First, an appropriate mathematical framework for representing subjective imprecision was identified. Then, the original LCC closed-form equation was reformulated so that uncertainties in all input parameters can be modelled in an effective and convenient manner. Finally, the formulated model was implemented in the form of an efficient computational algorithm. The algorithm handles a number of alternatives with imprecise input data and ranks them automatically. The solution of a selected example problem is included to clarify the theory of the model
Theory and Applications of Infinitesimal Dipole Models for Computational Electromagnetics
The recently introduced quantum particle swarm optimization (QPSO) algorithm
is employed to find infinitesimal dipole models (IDM) for antennas with known
near-fields (measured or computed). The IDM can predict accurately both the
near-fields and the far- fields of the antenna. A theory is developed to
explain the mechanism behind the IDM using the multipole expansion method. The
IDM obtained from single frequency solutions is extrapolated over a frequency
range around the design frequency. The method is demonstrated by analyzing
conductingand dielectric- type antennas. A calibration procedure is proposed to
systematically implement infinitesimal dipoles within existing MOM codes. The
interaction of the IDM with passive and active objects is studied through
several examples. The IDM proved to predict the interaction efficiently. A
closed-form expression for the mutual admittance between similar or dissimilar
antennas, with arbitrary orientations and/or locations, is derived using the
reaction theorem
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