605 research outputs found
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
Wireless Powered Dense Cellular Networks: How Many Small Cells Do We Need?
This paper focuses on wireless powered 5G dense cellular networks, where base
station (BS) delivers energy to user equipment (UE) via the microwave radiation
in sub-6 GHz or millimeter wave (mmWave) frequency, and UE uses the harvested
energy for uplink information transmission. By addressing the impacts of
employing different number of antennas and bandwidths at lower and higher
frequencies, we evaluate the amount of harvested energy and throughput in such
networks. Based on the derived results, we obtain the required small cell
density to achieve an expected level of harvested energy or throughput. Also,
we obtain that when the ratio of the number of sub-6 GHz BSs to that of the
mmWave BSs is lower than a given threshold, UE harvests more energy from a
mmWave BS than a sub-6 GHz BS. We find how many mmWave small cells are needed
to perform better than the sub-6 GHz small cells from the perspectives of
harvested energy and throughput. Our results reveal that the amount of
harvested energy from the mmWave tier can be comparable to the sub-6 GHz
counterpart in the dense scenarios. For the same tier scale, mmWave tier can
achieve higher throughput. Furthermore, the throughput gap between different
mmWave frequencies increases with the mmWave BS density.Comment: pages 1-14, accepted by IEEE Journal on Selected Areas in
Communication
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A stochastic geometry analysis of cooperative wireless networks powered by energy harvesting
textEnergy harvesting technology is essential for enabling green, sustainable and autonomous wireless networks. In this report, a large-scale wireless network with energy harvesting transmitters is considered, where a group of transmitters forms a cluster to cooperatively serve a desired user in the presence of co-channel interference and noise. Using stochastic geometry, simple closed-form expressions are derived to characterize the outage performance at the user as a function of important parameters such as the energy harvesting rate, the energy buffer size and the cluster size for a given cluster geometry. The analysis is further extended to characterize the delay due to transmission failure. The developed framework is flexible in that it allows the in-cluster transmitters to have possibly different energy harvesting capabilities. The analytical expressions are first validated using simulations and then used for investigating the impact of different parameters such as cluster and buffer size on outage performance. The results suggest that substantial outage performance can in fact be extracted with a relatively small energy buffer. Moreover, the utility of having a large energy buffer increases with the cluster size as well as with the energy harvesting rate.Electrical and Computer Engineerin
Mitigating Interference in Content Delivery Networks by Spatial Signal Alignment: The Approach of Shot-Noise Ratio
Multimedia content especially videos is expected to dominate data traffic in
next-generation mobile networks. Caching popular content at the network edge
has emerged to be a solution for low-latency content delivery. Compared with
the traditional wireless communication, content delivery has a key
characteristic that many signals coexisting in the air carry identical popular
content. They, however, can interfere with each other at a receiver if their
modulation-and-coding (MAC) schemes are adapted to individual channels
following the classic approach. To address this issue, we present a novel idea
of content adaptive MAC (CAMAC) where adapting MAC schemes to content ensures
that all signals carry identical content are encoded using an identical MAC
scheme, achieving spatial MAC alignment. Consequently, interference can be
harnessed as signals, to improve the reliability of wireless delivery. In the
remaining part of the paper, we focus on quantifying the gain CAMAC can bring
to a content-delivery network using a stochastic-geometry model. Specifically,
content helpers are distributed as a Poisson point process, each of which
transmits a file from a content database based on a given popularity
distribution. It is discovered that the successful content-delivery probability
is closely related to the distribution of the ratio of two independent shot
noise processes, named a shot-noise ratio. The distribution itself is an open
mathematical problem that we tackle in this work. Using stable-distribution
theory and tools from stochastic geometry, the distribution function is derived
in closed form. Extending the result in the context of content-delivery
networks with CAMAC yields the content-delivery probability in different closed
forms. In addition, the gain in the probability due to CAMAC is shown to grow
with the level of skewness in the content popularity distribution.Comment: 32 pages, to appear in IEEE Trans. on Wireless Communicatio
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