Terahertz Meets AI: The State of the Art
Terahertz (THz) is a promising technology for future wireless communication networks, particularly for 6G and beyond. The ultra-wide THz band, ranging from 0.1 to 10 THz, can potentially address the limited capacity and scarcity of spectrum in current wireless systems such as 4G-LTE and 5G. Furtherm...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/11/5034 |
| _version_ | 1797596777617031168 |
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| author | Arshad Farhad Jae-Young Pyun |
| author_facet | Arshad Farhad Jae-Young Pyun |
| author_sort | Arshad Farhad |
| collection | DOAJ |
| description | Terahertz (THz) is a promising technology for future wireless communication networks, particularly for 6G and beyond. The ultra-wide THz band, ranging from 0.1 to 10 THz, can potentially address the limited capacity and scarcity of spectrum in current wireless systems such as 4G-LTE and 5G. Furthermore, it is expected to support advanced wireless applications requiring high data transmission and quality services, i.e., terabit-per-second backhaul systems, ultra-high-definition streaming, virtual/augmented reality, and high-bandwidth wireless communications. In recent years, artificial intelligence (AI) has been used mainly for resource management, spectrum allocation, modulation and bandwidth classification, interference mitigation, beamforming, and medium access control layer protocols to improve THz performance. This survey paper examines the use of AI in state-of-the-art THz communications, discussing the challenges, potentials, and shortcomings. Additionally, this survey discusses the available platforms, including commercial, testbeds, and publicly available simulators for THz communications. Finally, this survey provides future strategies for improving the existing THz simulators and using AI methods, including deep learning, federated learning, and reinforcement learning, to improve THz communications. |
| first_indexed | 2024-03-11T02:57:49Z |
| format | Article |
| id | doaj.art-939259bea9cb4dfea3cdbb6a04b4661c |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T02:57:49Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-939259bea9cb4dfea3cdbb6a04b4661c2023-11-18T08:31:38ZengMDPI AGSensors1424-82202023-05-012311503410.3390/s23115034Terahertz Meets AI: The State of the ArtArshad Farhad0Jae-Young Pyun1Department of Information and Communication Engineering, Chosun University, Gwangju 61452, Republic of KoreaDepartment of Information and Communication Engineering, Chosun University, Gwangju 61452, Republic of KoreaTerahertz (THz) is a promising technology for future wireless communication networks, particularly for 6G and beyond. The ultra-wide THz band, ranging from 0.1 to 10 THz, can potentially address the limited capacity and scarcity of spectrum in current wireless systems such as 4G-LTE and 5G. Furthermore, it is expected to support advanced wireless applications requiring high data transmission and quality services, i.e., terabit-per-second backhaul systems, ultra-high-definition streaming, virtual/augmented reality, and high-bandwidth wireless communications. In recent years, artificial intelligence (AI) has been used mainly for resource management, spectrum allocation, modulation and bandwidth classification, interference mitigation, beamforming, and medium access control layer protocols to improve THz performance. This survey paper examines the use of AI in state-of-the-art THz communications, discussing the challenges, potentials, and shortcomings. Additionally, this survey discusses the available platforms, including commercial, testbeds, and publicly available simulators for THz communications. Finally, this survey provides future strategies for improving the existing THz simulators and using AI methods, including deep learning, federated learning, and reinforcement learning, to improve THz communications.https://www.mdpi.com/1424-8220/23/11/5034Terahertz (THz)artificial intelligence (AI)6GTHz MAC protocols6G and beyondTHz simulators |
| spellingShingle | Arshad Farhad Jae-Young Pyun Terahertz Meets AI: The State of the Art Sensors Terahertz (THz) artificial intelligence (AI) 6G THz MAC protocols 6G and beyond THz simulators |
| title | Terahertz Meets AI: The State of the Art |
| title_full | Terahertz Meets AI: The State of the Art |
| title_fullStr | Terahertz Meets AI: The State of the Art |
| title_full_unstemmed | Terahertz Meets AI: The State of the Art |
| title_short | Terahertz Meets AI: The State of the Art |
| title_sort | terahertz meets ai the state of the art |
| topic | Terahertz (THz) artificial intelligence (AI) 6G THz MAC protocols 6G and beyond THz simulators |
| url | https://www.mdpi.com/1424-8220/23/11/5034 |
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