Advancements in AI for 6G Networks: Technology, Standardization, and Future Prospects

被引:0
作者
Alanya-Beltran, Joel [1 ]
Silva-Cueva, Johan [2 ]
Hermitano-Atencio, Bernardo [3 ]
Cardenas-Palominio, Frans [4 ]
Alvarez-Huertas, Frank [5 ]
Poma-Garcia, Claudia [6 ]
机构
[1] Univ San Ignacio Loyola, Dept Engn, Lima, Peru
[2] Univ Nacl Educ Enrique Guzman & Valle, Acad Dept Elect & Telemat, Lima, Peru
[3] Univ Nacl Educ Enrique Guzman & Valle, Dept Elect & Telemat, Lima, Peru
[4] Univ Nacl Educ Enrique Guzman & Valle, Dept Sci, Lima, Peru
[5] Univ Nacl Mayor San Marcos, Dept Sci, Lima, Peru
[6] Univ Cesar Vallejo, Postgrad Dept, Trujillo, Peru
来源
2024 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATION AND APPLIED INFORMATICS, ACCAI 2024 | 2024年
关键词
Artificial Intelligence; 6G; Networks; Technology; Standardization;
D O I
10.1109/ACCAI61061.2024.10602082
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The commercial development of fifth generation (5G) mobile phone networks has begun. These systems provide a plethora of new prospects to a variety of businesses, as well as new services and enhanced user experiences for users. Yet there are still a lot of obstacles for 5G. In order to address these challenges, international industrial, academic, and standards organizations have started researching sixth generation (6G) wireless communication networks. The integration of terrestrial, aerial, with underwater communications into a dependable, fast, and ultra-low latency network capable of supporting a large number of devices is anticipated with the advent of the sixth-generation (6G) communication network. GNDO is compared with numerous recently developed algorithms. Power consumption is a key issue in sustainable green 6G-IBN, and the proposed method is employed to save it. The suggested algorithm exhibits competitive performance and qualities, as evidenced by the experimental results paired with descriptive statistics.
引用
收藏
页数:5
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