Self-Sustainable Communications With RF Energy Harvesting: Ginibre Point Process Modeling and Analysis
RF-enabled wireless power transfer and energy harvesting has recently emerged as a promising technique to provision perpetual energy replenishment for low-power wireless networks. The network devices are replenished by the RF energy harvested from the transmission of ambient RF transmitters, which o...
Saved in:
Main Authors: | , , , , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2016
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/84594 http://hdl.handle.net/10220/41884 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-84594 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-845942023-02-28T19:33:24Z Self-Sustainable Communications With RF Energy Harvesting: Ginibre Point Process Modeling and Analysis Lu, Xiao Flint, Ian Niyato, Dusit Privault, Nicolas Wang, Ping School of Physical and Mathematical Sciences Wireless energy harvesting self-sustainable communications RF-enabled wireless power transfer and energy harvesting has recently emerged as a promising technique to provision perpetual energy replenishment for low-power wireless networks. The network devices are replenished by the RF energy harvested from the transmission of ambient RF transmitters, which offers a practical and promising solution to enable self-sustainable communications. This paper adopts a stochastic geometry framework based on the Ginibre model to analyze the performance of self-sustainable communications over cellular networks with general fading channels. Specifically, we consider the point-to-point downlink transmission between an access point and a battery-free device in the cellular networks, where the ambient RF transmitters are randomly distributed following a repulsive point process, called Ginibre α-determinantal point process (DPP). Two practical RF energy harvesting receiver architectures, namely time-switching and power-splitting, are investigated. We perform an analytical study on the RF-powered device and derive the expectation of the RF energy harvesting rate, the energy outage probability and the transmission outage probability over Nakagami-m fading channels. These are expressed in terms of so-called Fredholm determinants, which we compute efficiently with modern techniques from numerical analysis. Our analytical results are corroborated by the numerical simulations, and the efficiency of our approximations is demonstrated. In practice, the accurate simulation of any of the Fredholm determinant appearing in the manuscript is a matter of seconds. An interesting finding is that a smaller value of α (corresponding to larger repulsion) yields a better transmission outage performance when the density of the ambient RF transmitters is small. However, it yields a lower transmission outage probability when the density of the ambient RF transmitters is large. We also show analytically that the power-splitting architecture outperforms the time-switching architecture in terms of transmission outage performances. Lastly, our analysis provides guidelines for setting the time-switching and power-splitting coefficients at their optimal values. Accepted version 2016-12-19T06:44:53Z 2019-12-06T15:47:57Z 2016-12-19T06:44:53Z 2019-12-06T15:47:57Z 2016 Journal Article Lu, X., Flint, I., Niyato, D., Privault, N., & Wang, P. (2016). Self-Sustainable Communications With RF Energy Harvesting: Ginibre Point Process Modeling and Analysis. IEEE Journal on Selected Areas in Communications, 34(5), 1518-1535. 0733-8716 https://hdl.handle.net/10356/84594 http://hdl.handle.net/10220/41884 10.1109/JSAC.2016.2551538 en IEEE Journal on Selected Areas in Communications © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/JSAC.2016.2551538]. 18 p. application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
Wireless energy harvesting self-sustainable communications |
spellingShingle |
Wireless energy harvesting self-sustainable communications Lu, Xiao Flint, Ian Niyato, Dusit Privault, Nicolas Wang, Ping Self-Sustainable Communications With RF Energy Harvesting: Ginibre Point Process Modeling and Analysis |
description |
RF-enabled wireless power transfer and energy harvesting has recently emerged as a promising technique to provision perpetual energy replenishment for low-power wireless networks. The network devices are replenished by the RF energy harvested from the transmission of ambient RF transmitters, which offers a practical and promising solution to enable self-sustainable communications. This paper adopts a stochastic geometry framework based on the Ginibre model to analyze the performance of self-sustainable communications over cellular networks with general fading channels. Specifically, we consider the point-to-point downlink transmission between an access point and a battery-free device in the cellular networks, where the ambient RF transmitters are randomly distributed following a repulsive point process, called Ginibre α-determinantal point process (DPP). Two practical RF energy harvesting receiver architectures, namely time-switching and power-splitting, are investigated. We perform an analytical study on the RF-powered device and derive the expectation of the RF energy harvesting rate, the energy outage probability and the transmission outage probability over Nakagami-m fading channels. These are expressed in terms of so-called Fredholm determinants, which we compute efficiently with modern techniques from numerical analysis. Our analytical results are corroborated by the numerical simulations, and the efficiency of our approximations is demonstrated. In practice, the accurate simulation of any of the Fredholm determinant appearing in the manuscript is a matter of seconds. An interesting finding is that a smaller value of α (corresponding to larger repulsion) yields a better transmission outage performance when the density of the ambient RF transmitters is small. However, it yields a lower transmission outage probability when the density of the ambient RF transmitters is large. We also show analytically that the power-splitting architecture outperforms the time-switching architecture in terms of transmission outage performances. Lastly, our analysis provides guidelines for setting the time-switching and power-splitting coefficients at their optimal values. |
author2 |
School of Physical and Mathematical Sciences |
author_facet |
School of Physical and Mathematical Sciences Lu, Xiao Flint, Ian Niyato, Dusit Privault, Nicolas Wang, Ping |
format |
Article |
author |
Lu, Xiao Flint, Ian Niyato, Dusit Privault, Nicolas Wang, Ping |
author_sort |
Lu, Xiao |
title |
Self-Sustainable Communications With RF Energy Harvesting: Ginibre Point Process Modeling and Analysis |
title_short |
Self-Sustainable Communications With RF Energy Harvesting: Ginibre Point Process Modeling and Analysis |
title_full |
Self-Sustainable Communications With RF Energy Harvesting: Ginibre Point Process Modeling and Analysis |
title_fullStr |
Self-Sustainable Communications With RF Energy Harvesting: Ginibre Point Process Modeling and Analysis |
title_full_unstemmed |
Self-Sustainable Communications With RF Energy Harvesting: Ginibre Point Process Modeling and Analysis |
title_sort |
self-sustainable communications with rf energy harvesting: ginibre point process modeling and analysis |
publishDate |
2016 |
url |
https://hdl.handle.net/10356/84594 http://hdl.handle.net/10220/41884 |
_version_ |
1759856255308922880 |