4 research outputs found
A Stochastic Geometry Analysis of Energy Harvesting in Large Scale Wireless Networks
In this paper, the theoretical sustainable capacity of wireless networks with
radio frequency (RF) energy harvesting is analytically studied. Specifically,
we consider a large scale wireless network where base stations (BSs) and low
power wireless devices are deployed by homogeneous Poisson point process (PPP)
with different spatial densities. Wireless devices exploit the downlink
transmissions from the BSs for either information delivery or energy
harvesting. Generally, a BS schedules downlink transmission to wireless
devices. The scheduled device receives the data information while other devices
harvest energy from the downlink signals. The data information can be
successfully received by the scheduled device only if the device has sufficient
energy for data processing, i.e., the harvested energy is larger than a
threshold. Given the densities of BSs and users, we apply stochastic geometry
to analyze the expected number of users per cell and the successful information
delivery probability of a wireless device, based on which the total network
throughput can be derived. It is shown that the maximum network throughput per
cell can be achieved under the optimal density of BSs. Extensive simulations
validate the analysis.Comment: This paper has been accepted by Greencom 201
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
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
Joint Energy and SINR Coverage in Spatially Clustered RF-powered IoT Network
Owing to the ubiquitous availability of radio-frequency (RF) signals, RF
energy harvesting is emerging as an appealing solution for powering IoT
devices. In this paper, we model and analyze an IoT network which harvests RF
energy and receives information from the same wireless network. In order to
enable this operation, each time slot is partitioned into charging and
information reception phases. For this setup, we characterize two performance
metrics: (i) energy coverage and (ii) joint signal-to-interference-plus-noise
(SINR) and energy coverage. The analysis is performed using a realistic spatial
model that captures the spatial coupling between the locations of the IoT
devices and the nodes of the wireless network (referred henceforth as the IoT
gateways), which is often ignored in the literature. In particular, we model
the locations of the IoT devices using a Poisson cluster process (PCP) and
assume that some of the clusters have IoT gateways (GWs) deployed at their
centers while the other GWs are deployed independently of the IoT devices. The
level of coupling can be controlled by tuning the fraction of total GWs that
are deployed at the cluster centers. Due to the inherent intractability of
computing the distribution of shot noise process for this setup, we propose two
accurate approximations, using which the aforementioned metrics are
characterized. Multiple system design insights are drawn from our results. For
instance, we demonstrate the existence of optimal slot partitioning that
maximizes the system throughput. In addition, we explore the effect of the
level of coupling between the locations of the IoT devices and the GWs on this
optimal slot partitioning. Particularly, our results reveal that the optimal
value of time duration for the charging phase increases as the level of
coupling decreases.Comment: To appear in IEEE Transactions on Green Communications and Networkin