Kishk, Mustafa A. and Dhillon, Harpreet S. (2018) Joint Uplink and Downlink Coverage Analysis of Cellular-based RF-powered IoT Network. IEEE Transactions on Green Communications and Networking, 2 (2). pp. 446-459. ISSN 2473-2400
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Abstract
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: 1) 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; 2) downlink sub-slot during which the IoT device
receives information from the associated BS; and 3) uplink subslot 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.
Item Type: | Article |
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Keywords: | Stochastic geometry; Internet of Things; ambient RF energy harvesting; cellular network; Poisson point process; |
Academic Unit: | Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: | 17003 |
Identification Number: | 10.1109/TGCN.2017.2786694 |
Depositing User: | Mustafa Kishk |
Date Deposited: | 08 Mar 2023 14:28 |
Journal or Publication Title: | IEEE Transactions on Green Communications and Networking |
Publisher: | Institute of Electrical and Electronics Engineers |
Refereed: | Yes |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/17003 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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