Driving 5G Mobile Communications with Artificial Intelligence towards 6G

以人工智能推动5G移动通信迈向6G

工程热物理

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作      者
出  版 社
出版时间
2023年04月06日
装      帧
精装
ISBN
9781032071244
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页      码
488
开      本
234 x 156 mm (6.14 x 9.21
语      种
英文
版      次
1
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图书简介
Driving 5G Mobile Communications with Artificial Intelligence towards 6G presents current work and directions of continuously innovation and development in multimedia communications with a focus on services and users. The fifth generation of mobile wireless networks achieved the first deployment by 2020, completed the first phase of evolution in 2022, and started transition phase of 5G-Advanced toward the sixth generation. Perhaps one of the most important innovations brought by 5G is the platform-approach to connectivity, i.e., a single standard that can adapt to the heterogeneous connectivity requirements of vastly different use cases. 5G networks contain a list of different requirements, standardized technical specifications and a range of implementation options with spectral efficiency, latency, and reliability as primary performance metrics. Towards 6G, machine learning (ML) and artificial intelligence (AI) methods have recently proposed new approaches to modeling, designing, optimizing and implementing systems. They are now matured technologies that improve many research fields significantly.The area of wireless multimedia communications has developed immensely, generating a large number of concepts, ideas, technical specifications, mobile standards, patents, and articles. Identifying the basic ideas and their complex interconnections becomes increasingly important.The book is divided into three major parts, with each part containing four or five chapters:Advanced 5G communicationMachine learning-based communication and network automationArtificial Intelligence towards 6GThe first part discusses three main scenarios and standard specification of 5G use cases (eMBB, URLLC, mMTC), vehicular systems beyond 5G, and efficient edge architecture on NFV infrastructure. In the second part, different AI/ML-based methodologies and open research challenges are presented in introducing 5G-AIoT
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