Energy-Efficient Cooperative MIMO Formation for Underwater MI-Assisted Acoustic Wireless Sensor Networks
The energy problem has become one of the critical factors limiting the development of underwater wireless sensor networks (UWSNs), and cooperative multiple-input–multiple-output (MIMO) technology has shown advantages in energy saving. However, the design of energy-efficient cooperative MIMO techniqu...
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MDPI AG
2022-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/15/3641 |
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| author | Qingyan Ren Yanjing Sun Tingting Wang Beibei Zhang |
| author_facet | Qingyan Ren Yanjing Sun Tingting Wang Beibei Zhang |
| author_sort | Qingyan Ren |
| collection | DOAJ |
| description | The energy problem has become one of the critical factors limiting the development of underwater wireless sensor networks (UWSNs), and cooperative multiple-input–multiple-output (MIMO) technology has shown advantages in energy saving. However, the design of energy-efficient cooperative MIMO techniques does not consider the actual underwater environment, such as the distribution of nodes. Underwater magnetic induction (MI)-assisted acoustic cooperative MIMO WSNs as a promising scheme in throughput, signal-to-noise ratio (SNR), and connectivity have been demonstrated. In this paper, the potential of the networks to reduce energy consumption is further explored through the joint use of cooperative MIMO and data aggregation, and a cooperative MIMO formation scheme is presented to make the network more energy efficient. For this purpose, we first derive a mathematical model to analyze the energy consumption during data transmission, considering the correlation between data generated by nodes. Based on this model, we proposed a cooperative MIMO size optimization algorithm, which considers the expected transmission distance and transmission power constraints. Moreover, a competitive cooperative MIMO formation algorithm that jointly designs master node (MN) selection and cooperative MIMO size can improve energy efficiency and guarantee the connectivity of underwater nodes and surface base station (BS). Our simulation results confirm that the proposed scheme achieves significant energy savings and prolongs the network lifetime considerably. |
| first_indexed | 2024-03-09T12:13:45Z |
| format | Article |
| id | doaj.art-51e4669cbb32492d8cfc531c08a50edf |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T12:13:45Z |
| publishDate | 2022-07-01 |
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| series | Remote Sensing |
| spelling | doaj.art-51e4669cbb32492d8cfc531c08a50edf2023-11-30T22:48:45ZengMDPI AGRemote Sensing2072-42922022-07-011415364110.3390/rs14153641Energy-Efficient Cooperative MIMO Formation for Underwater MI-Assisted Acoustic Wireless Sensor NetworksQingyan Ren0Yanjing Sun1Tingting Wang2Beibei Zhang3School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaThe energy problem has become one of the critical factors limiting the development of underwater wireless sensor networks (UWSNs), and cooperative multiple-input–multiple-output (MIMO) technology has shown advantages in energy saving. However, the design of energy-efficient cooperative MIMO techniques does not consider the actual underwater environment, such as the distribution of nodes. Underwater magnetic induction (MI)-assisted acoustic cooperative MIMO WSNs as a promising scheme in throughput, signal-to-noise ratio (SNR), and connectivity have been demonstrated. In this paper, the potential of the networks to reduce energy consumption is further explored through the joint use of cooperative MIMO and data aggregation, and a cooperative MIMO formation scheme is presented to make the network more energy efficient. For this purpose, we first derive a mathematical model to analyze the energy consumption during data transmission, considering the correlation between data generated by nodes. Based on this model, we proposed a cooperative MIMO size optimization algorithm, which considers the expected transmission distance and transmission power constraints. Moreover, a competitive cooperative MIMO formation algorithm that jointly designs master node (MN) selection and cooperative MIMO size can improve energy efficiency and guarantee the connectivity of underwater nodes and surface base station (BS). Our simulation results confirm that the proposed scheme achieves significant energy savings and prolongs the network lifetime considerably.https://www.mdpi.com/2072-4292/14/15/3641heterogeneous underwater wireless sensor networkscooperative MIMOdata aggregationenergy efficiency |
| spellingShingle | Qingyan Ren Yanjing Sun Tingting Wang Beibei Zhang Energy-Efficient Cooperative MIMO Formation for Underwater MI-Assisted Acoustic Wireless Sensor Networks Remote Sensing heterogeneous underwater wireless sensor networks cooperative MIMO data aggregation energy efficiency |
| title | Energy-Efficient Cooperative MIMO Formation for Underwater MI-Assisted Acoustic Wireless Sensor Networks |
| title_full | Energy-Efficient Cooperative MIMO Formation for Underwater MI-Assisted Acoustic Wireless Sensor Networks |
| title_fullStr | Energy-Efficient Cooperative MIMO Formation for Underwater MI-Assisted Acoustic Wireless Sensor Networks |
| title_full_unstemmed | Energy-Efficient Cooperative MIMO Formation for Underwater MI-Assisted Acoustic Wireless Sensor Networks |
| title_short | Energy-Efficient Cooperative MIMO Formation for Underwater MI-Assisted Acoustic Wireless Sensor Networks |
| title_sort | energy efficient cooperative mimo formation for underwater mi assisted acoustic wireless sensor networks |
| topic | heterogeneous underwater wireless sensor networks cooperative MIMO data aggregation energy efficiency |
| url | https://www.mdpi.com/2072-4292/14/15/3641 |
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