O. M. Rosabal, O. L. A. López, H. Alves, S. Montejo-Sánchez and M. Latva-aho, "On the Optimal Deployment of Power Beacons for Massive Wireless Energy Transfer," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2020.3048065
On the optimal deployment of power beacons for massive wireless energy transfer
|Author:||Rosabal, Osmel Martínez1; Alcaraz López, Onel L.1; Alves, Hirley1;|
1Centre of wireless Communications (CWC), University of Oulu, Finland
2Programa Institucional de Fomento a la I+D+i, Universidad Tecnológica Metropolitana, Santiago 8940577, Chile
|Online Access:||PDF Full Text (PDF, 1.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202103056640
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2021-03-05
Wireless energy transfer (WET) is emerging as an enabling green technology for Internet of Things (IoT) networks. WET allows the IoT devices to wirelessly recharge their batteries with energy from external sources such as dedicated radio frequency transmitters called power beacons (PBs). In this paper, we investigate the optimal deployment of PBs that guarantees a network-wide energy outage constraint. Optimal positions for the PBs are determined by maximizing the average incident power for the worst location in the service area since no information about the sensor deployment is provided. Such network planning guarantees the fairest harvesting performance for all the IoT devices. Numerical simulations evidence that our proposed optimization framework improves the energy supply reliability compared to benchmark schemes. Additionally, we show that although both, the number of deployed PBs and the number of antennas per PB, introduce performance improvements, the former has a dominant role. Finally, our proposal allows to extend the coverage area while keeping the total power budget fixed, which additionally reduces the level of electromagnetic radiation in the vicinity of PBs.
IEEE internet of things journal
|Pages:||1 - 11|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This research has been financially supported by Academy of Finland, 6Genesis Flagship (Grant n.318927), EE-IoT (n.319008), Aka Prof (n.307492), as well as FONDECYT Iniciaci´on No. 11200659, FONDECYT Regular No. 1201893, and FONDEQUIP EQM180180.
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
319008 (Academy of Finland Funding decision)
307492 (Academy of Finland Funding decision)
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