作者
Hao Song, Jianan Bai, Yang Yi, Jinsong Wu, Lingjia Liu
发表日期
2020/1/10
期刊
IEEE Computational Intelligence Magazine
卷号
15
期号
1
页码范围
44-51
出版商
IEEE
简介
The explosive growth of wireless devices motivates the development of the internet-of-things (IoT), which is capable of interconnecting massive and diverse "things" via wireless communications. This is also called massive machine type communications (mMTC) as a part of the undergoing fifth generation (5G) mobile networks. It is envisioned that more sophisticated devices would be connected to form a hyperconnected world with the aids of the sixth generation (6G) mobile networks. To enable wireless accesses of such IoT networks, artificial intelligence (AI) can play an important role. In this article, the frameworks of centralized and distributed AI-enabled IoT networks are introduced. Key technical challenges, including random access and spectrum sharing (spectrum access and spectrum sensing), are analyzed for different network architectures. Deep reinforcement learning (DRL)-based strategies are introduced …
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