Statistical Characterization of Wireless Power Transfer via Unmodulated Emission
In the past few years, the ability to transfer power wirelessly has experienced growing interest from the research community. Because the wireless channel is subject to a large number of random phenomena, a crucial aspect is the statistical characterization of the energy that can be harvested by a g...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/20/7828 |
| _version_ | 1797469985399898112 |
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| author | Sebastià Galmés |
| author_facet | Sebastià Galmés |
| author_sort | Sebastià Galmés |
| collection | DOAJ |
| description | In the past few years, the ability to transfer power wirelessly has experienced growing interest from the research community. Because the wireless channel is subject to a large number of random phenomena, a crucial aspect is the statistical characterization of the energy that can be harvested by a given device. For this characterization to be reliable, a powerful model of the propagation channel is necessary. The recently proposed generalized-K model has proven to be very useful, as it encompasses the effects of path loss, shadowing, and fast fading for a broad set of wireless scenarios, and because it is analytically tractable. Accordingly, the purpose of this paper is to characterize, from a statistical point of view, the energy harvested by a static device from an unmodulated carrier signal generated by a dedicated source, assuming that the wireless channel obeys the generalized-K propagation model. Specifically, by using simulation-validated analytical methods, this paper provides exact closed-form expressions for the average and variance of the energy harvested over an arbitrary time period. The derived formulation can be used to determine a power transfer plan that allows multiple or even massive numbers of low-power devices to operate continuously, as expected from future network scenarios such as the Internet of things or 5G/6G. |
| first_indexed | 2024-03-09T19:30:26Z |
| format | Article |
| id | doaj.art-1a5e929173b74007abd1551695241138 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T19:30:26Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-1a5e929173b74007abd15516952411382023-11-24T02:26:52ZengMDPI AGSensors1424-82202022-10-012220782810.3390/s22207828Statistical Characterization of Wireless Power Transfer via Unmodulated EmissionSebastià Galmés0Departament de Ciències Matemàtiques i Informàtica, Universitat de les Illes Balears, 07122 Palma, SpainIn the past few years, the ability to transfer power wirelessly has experienced growing interest from the research community. Because the wireless channel is subject to a large number of random phenomena, a crucial aspect is the statistical characterization of the energy that can be harvested by a given device. For this characterization to be reliable, a powerful model of the propagation channel is necessary. The recently proposed generalized-K model has proven to be very useful, as it encompasses the effects of path loss, shadowing, and fast fading for a broad set of wireless scenarios, and because it is analytically tractable. Accordingly, the purpose of this paper is to characterize, from a statistical point of view, the energy harvested by a static device from an unmodulated carrier signal generated by a dedicated source, assuming that the wireless channel obeys the generalized-K propagation model. Specifically, by using simulation-validated analytical methods, this paper provides exact closed-form expressions for the average and variance of the energy harvested over an arbitrary time period. The derived formulation can be used to determine a power transfer plan that allows multiple or even massive numbers of low-power devices to operate continuously, as expected from future network scenarios such as the Internet of things or 5G/6G.https://www.mdpi.com/1424-8220/22/20/7828radio-frequency energy harvestingwireless power transferpath lossshadowingmulti-path fadingunmodulated carrier |
| spellingShingle | Sebastià Galmés Statistical Characterization of Wireless Power Transfer via Unmodulated Emission Sensors radio-frequency energy harvesting wireless power transfer path loss shadowing multi-path fading unmodulated carrier |
| title | Statistical Characterization of Wireless Power Transfer via Unmodulated Emission |
| title_full | Statistical Characterization of Wireless Power Transfer via Unmodulated Emission |
| title_fullStr | Statistical Characterization of Wireless Power Transfer via Unmodulated Emission |
| title_full_unstemmed | Statistical Characterization of Wireless Power Transfer via Unmodulated Emission |
| title_short | Statistical Characterization of Wireless Power Transfer via Unmodulated Emission |
| title_sort | statistical characterization of wireless power transfer via unmodulated emission |
| topic | radio-frequency energy harvesting wireless power transfer path loss shadowing multi-path fading unmodulated carrier |
| url | https://www.mdpi.com/1424-8220/22/20/7828 |
| work_keys_str_mv | AT sebastiagalmes statisticalcharacterizationofwirelesspowertransferviaunmodulatedemission |