面向 6G 的人工智能多址接入:频谱感知、协议设计与优化概览

IF 23.2 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Xuelin Cao;Bo Yang;Kaining Wang;Xinghua Li;Zhiwen Yu;Chau Yuen;Yan Zhang;Zhu Han
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引用次数: 0

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本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI-Empowered Multiple Access for 6G: A Survey of Spectrum Sensing, Protocol Designs, and Optimizations
With the rapidly increasing number of bandwidth-intensive terminals capable of intelligent computing and communication, such as smart devices equipped with shallow neural network (NN) models, the complexity of multiple access (MA) for these intelligent terminals is increasing due to the dynamic network environment and ubiquitous connectivity in sixth-generation (6G) systems. Traditional MA design and optimization methods are gradually losing ground to artificial intelligence (AI) techniques that have proven their superiority in handling complexity. AI-empowered MA and its optimization strategies aimed at achieving high quality-of-service (QoS) are attracting more attention, especially in the area of latency-sensitive applications in 6G systems. In this work, we aim to: 1) present the development and comparative evaluation of AI-enabled MA; 2) provide a timely survey focusing on spectrum sensing, protocol design, and optimization for AI-empowered MA; and 3) explore the potential use cases of AI-empowered MA in the typical application scenarios within 6G systems. Specifically, we first present a unified framework of AI-empowered MA for 6G systems by incorporating various promising machine learning (ML) techniques in spectrum sensing, resource allocation, MA protocol design, and optimization. We then introduce AI-empowered MA spectrum sensing related to spectrum sharing and spectrum interference management. Next, we discuss the AI-empowered MA protocol designs and implementation methods by reviewing and comparing the state of the art and further explore the optimization algorithms related to dynamic resource management, parameter adjustment, and access scheme switching. Finally, we discuss the current challenges, point out open issues, and outline potential future research directions in this field.
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来源期刊
Proceedings of the IEEE
Proceedings of the IEEE 工程技术-工程:电子与电气
CiteScore
46.40
自引率
1.00%
发文量
160
审稿时长
3-8 weeks
期刊介绍: Proceedings of the IEEE is the leading journal to provide in-depth review, survey, and tutorial coverage of the technical developments in electronics, electrical and computer engineering, and computer science. Consistently ranked as one of the top journals by Impact Factor, Article Influence Score and more, the journal serves as a trusted resource for engineers around the world.
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