Revisiting Information Detection and Energy Harvesting: A Power Splitting-Based Approach
Wireless sensors are becoming essential in machine-type communications and Internet of Things. As the key performance metrics, the spectral efficiency as well as the energy efficiency have been considered while determining the effectiveness of sensor networks. In this paper, we present several power...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/22/12/1341 |
| _version_ | 1797546690495905792 |
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| author | Jaehong Kim Won-Yong Shin Xin Kang Han Lim Lee Jingon Joung |
| author_facet | Jaehong Kim Won-Yong Shin Xin Kang Han Lim Lee Jingon Joung |
| author_sort | Jaehong Kim |
| collection | DOAJ |
| description | Wireless sensors are becoming essential in machine-type communications and Internet of Things. As the key performance metrics, the spectral efficiency as well as the energy efficiency have been considered while determining the effectiveness of sensor networks. In this paper, we present several power-splitting solutions to maximize the average harvested energy under a rate constraint when both the information and power are transmitted through the same wireless channel to a sensor (i.e., a receiver). More specifically, we first designed the optimal dynamic power-splitting policy, which decides the optimal fractional power of the received signal used for energy harvesting at the receiver. As effective solutions, we proposed two types of single-threshold-based power-splitting policies, namely, Policies I and II, which decide to switch between energy harvesting and information decoding by comparing the received signal power with some given thresholds. Additionally, we performed asymptotic analysis for a large number of packets along with practical statistics-based policies. Consequently, we demonstrated the effectiveness of the proposed power-splitting solutions in terms of the rate–energy trade-off. |
| first_indexed | 2024-03-10T14:32:49Z |
| format | Article |
| id | doaj.art-343c637794564b69ba30d3dded3a266e |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T14:32:49Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-343c637794564b69ba30d3dded3a266e2023-11-20T22:24:20ZengMDPI AGEntropy1099-43002020-11-012212134110.3390/e22121341Revisiting Information Detection and Energy Harvesting: A Power Splitting-Based ApproachJaehong Kim0Won-Yong Shin1Xin Kang2Han Lim Lee3Jingon Joung4School of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, KoreaDepartment of Computational Science and Engineering, Yonsei University, Seoul 03722, KoreaCenter for Intelligent Networking and Communications (CINC), University of Electronic Science and Technology of China (UESTC), Chengdu 611731, ChinaSchool of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, KoreaSchool of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, KoreaWireless sensors are becoming essential in machine-type communications and Internet of Things. As the key performance metrics, the spectral efficiency as well as the energy efficiency have been considered while determining the effectiveness of sensor networks. In this paper, we present several power-splitting solutions to maximize the average harvested energy under a rate constraint when both the information and power are transmitted through the same wireless channel to a sensor (i.e., a receiver). More specifically, we first designed the optimal dynamic power-splitting policy, which decides the optimal fractional power of the received signal used for energy harvesting at the receiver. As effective solutions, we proposed two types of single-threshold-based power-splitting policies, namely, Policies I and II, which decide to switch between energy harvesting and information decoding by comparing the received signal power with some given thresholds. Additionally, we performed asymptotic analysis for a large number of packets along with practical statistics-based policies. Consequently, we demonstrated the effectiveness of the proposed power-splitting solutions in terms of the rate–energy trade-off.https://www.mdpi.com/1099-4300/22/12/1341energy efficiencyenergy harvestinginformation decodingpower-splittingoptimal policy |
| spellingShingle | Jaehong Kim Won-Yong Shin Xin Kang Han Lim Lee Jingon Joung Revisiting Information Detection and Energy Harvesting: A Power Splitting-Based Approach Entropy energy efficiency energy harvesting information decoding power-splitting optimal policy |
| title | Revisiting Information Detection and Energy Harvesting: A Power Splitting-Based Approach |
| title_full | Revisiting Information Detection and Energy Harvesting: A Power Splitting-Based Approach |
| title_fullStr | Revisiting Information Detection and Energy Harvesting: A Power Splitting-Based Approach |
| title_full_unstemmed | Revisiting Information Detection and Energy Harvesting: A Power Splitting-Based Approach |
| title_short | Revisiting Information Detection and Energy Harvesting: A Power Splitting-Based Approach |
| title_sort | revisiting information detection and energy harvesting a power splitting based approach |
| topic | energy efficiency energy harvesting information decoding power-splitting optimal policy |
| url | https://www.mdpi.com/1099-4300/22/12/1341 |
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